Contemporary Gleason Grading of Prostatic Carcinoma: An Update With Discussion on Practical Issues to Implement the 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma

Machine learning discrimination of Gleason scores below GG3 and above GG4 for HSPC patients diagnosis

This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively collected data from 717 hormone-sensitive prostate cancer (HSPC) patients at Yunnan Cancer Hospital. Of these, data from 526 patients were used for modeling. Seven auxiliary models were established using Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Extreme gradient boosting tree (XGBoost), Adaptive Boosting (Adaboost), and artificial neural network (ANN) based on 21 clinical biochemical indicators and features. Evaluation metrics included accuracy (ACC), precision (PRE), specificity (SPE), sensitivity (SEN) or regression rate(Recall), and f1 score. Evaluation metrics for the models primarily included ACC, PRE, SPE, SEN or Recall, f1 score, and area under the curve(AUC). Evaluation metrics were visualized using confusion matrices and ROC curves. Among the ensemble learning methods, RF, XGBoost, and Adaboost performed the best. RF achieved a training dataset score of 0.769 (95% CI: 0.759-0.835) and a testing dataset score of 0.755 (95% CI: 0.660-0.760) (AUC: 0.786, 95%CI: 0.722-0.803), while XGBoost achieved a training dataset score of 0.755 (95% CI: 95%CI: 0.711-0.809) and a testing dataset score of 0.745 (95% CI: 0.660-0.764) (AUC: 0.777, 95% CI: 0.726-0.798). Adaboost scored 0.789 on the training dataset (95% CI: 0.782-0.857) and 0.774 on the testing dataset (95% CI: 0.651-0.774) (AUC: 0.799, 95% CI: 0.703-0.802). In terms of feature importance (FI) in ensemble learning, Bone metastases at first visit, prostatic volume, age, and T1-T2 have significant proportions in RF's FI. fPSA, TPSA, and tumor burden have significant proportions in Adaboost's FI, while f/TPSA, LDH, and testosterone have the highest proportions in XGBoost. Our findings indicate that ensemble learning methods demonstrate good performance in classifying HSPC patient data, with TNM staging and fPSA being important classification indicators. These discoveries provide valuable references for distinguishing different Gleason scores, facilitating more accurate patient assessments and personalized treatment plans.

Proposal for an optimised definition of adverse pathology (unfavourable histology) that predicts metastatic risk in prostatic adenocarcinoma independent of grade group and pathological stage

AIMS

Histological grading of prostate cancer is a powerful prognostic tool, but current criteria for grade assignment are not fully optimised. Our goal was to develop and test a simplified histological grading model, based heavily on large cribriform/intraductal carcinoma, with optimised sensitivity for predicting metastatic potential.

METHODS AND RESULTS

Two separate non-overlapping cohorts were identified: a 419-patient post-radical prostatectomy cohort with long term clinical follow-up and a 209-patient post-radical prostatectomy cohort in which all patients had pathologically confirmed metastatic disease. All prostatectomies were re-reviewed for high-risk histological patterns of carcinoma termed 'unfavourable histology'. Unfavourable histology is defined by any classic Gleason pattern 5 component, any large cribriform morphology (> 0.25 mm) or intraductal carcinoma, complex intraluminal papillary architecture, grade 3 stromogenic carcinoma and complex anastomosing cord-like growth. For the outcome cohort, Kaplan-Meier analysis compared biochemical recurrence, metastasis and death between subjects with favourable and unfavourable histology, stratified by pathological stage and grade group. Multivariable Cox proportional hazards models evaluated adding unfavourable histology to the Memorial Sloan Kettering Cancer Center (MSKCC) post-prostatectomy nomogram and stratification by percentage of unfavourable histology. At 15 years unfavourable histology predicted biochemical recurrence, with sensitivity of 93% and specificity of 88%, metastatic disease at 100 and 48% and death at 100 and 46%. Grade group 2 prostate cancers with unfavourable histology were associated with metastasis independent of pathological stage, while those without had no risk. Histological models for prediction of metastasis based on only large cribriform/intraductal carcinoma or increasing diameter of cribriform size improved specificity, but with lower sensitivity. Multivariable Cox proportional hazards models demonstrated that unfavourable histology significantly improved discriminatory power of the MSKCC post-prostatectomy nomogram for biochemical failure (likelihood ratio test P < 0.001). In the retrospective review of a separate RP cohort in which all patients had confirmed metastatic disease, none had unequivocal favourable histology.

CONCLUSIONS

Unfavourable histology at radical prostatectomy is associated with metastatic risk, predicted adverse outcomes better than current grading and staging systems and improved the MSKCC post-prostatectomy nomogram. Most importantly, unfavourable histology stratified grade group 2 prostate cancers into those with and without metastatic potential, independent of stage. While unfavourable histology is driven predominantly by large cribriform/intraductal carcinoma, the recognition and inclusion of other specific architectural patterns add to the sensitivity for predicting metastatic disease. Moreover, a simplified dichotomous model improves communication and could increase implementation.

Prognostic significance of invasive cribriform gland size and percentage in Gleason score 7 prostate adenocarcinoma

OBJECTIVES

Cribriform glands are linked to poorer outcomes in prostate adenocarcinoma. We aimed to assess the prognostic role of the percentage of cribriform glands and the size of the largest invasive cribriform gland in Gleason score 7 prostate adenocarcinomas.

METHODS

The presence, percentage, and size of the invasive cribriform glands were investigated and their association with prognostic factors were assessed in 177 Grade Groups 2 and 3 prostate adenocarcinomas.

RESULTS

Biochemical recurrence-free survival was statistically significantly lower in cases with a cribriform gland percentage greater than 10% (P < .001) and in cases where the largest invasive cribriform gland size was greater than 0.5 mm (P < .001). Mean largest cribriform gland size and percentage were statistically significant associated with more advanced pT status, lymph node metastasis, biochemical recurrence, and higher preoperative prostate-specific antigen values.

CONCLUSIONS

Our findings suggest that the presence of a cribriform pattern, increases in the percentage of such patterns, and increases in the size of the largest cribriform gland within a given tumor are associated with poor prognosis. We suggest that a more aggressive clinical approach may be needed in Grade Group 2 and 3 cases with invasive cribriform glands larger than 0.5 mm and a cribriform gland percentage greater than 10%, especially in prostate needle biopsy specimens.

UPCARE: Urinary Extracellular Vesicles-Derived Prostate Cancer Assessment for Risk Evaluation

In the quest for efficient tumor diagnosis via liquid biopsy, extracellular vesicles (EVs) have shown promise as a source of potential biomarkers. This study addresses the gap in biomarker efficacy for predicting clinically significant prostate cancer (csPCa) between the Western and Chinese populations. We developed a urinary extracellular vesicles-based prostate score (EPS) model, utilizing the EXODUS technique for EV isolation from 598 patients and incorporating gene expressions of FOXA1, PCA3, and KLK3. Our findings reveal that the EPS model surpasses prostate-specific antigen (PSA) testing in diagnostic accuracy within a training cohort of 234 patients, achieving an area under the curve (AUC) of 0.730 compared to 0.659 for PSA (p = 0.018). Similarly, in a validation cohort of 101 men, the EPS model achieved an AUC of 0.749, which was significantly better than PSA's 0.577 (p < 0.001). Our model has demonstrated a potential reduction in unnecessary prostate biopsies by 26%, with only a 3% miss rate for csPCa cases, indicating its effectiveness in the Chinese population.

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Background

Distinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading.

Purpose

This study aimed to quantify the CTRW parameters (α, β & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions.

Study type

Retrospective (retrospective analysis using prospective designed data).

Population

Thirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64-91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46-79 years).

Field strength/Sequence

MRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2).

Assessment

CTRW parameters and ADC were quantified in PCa and CP lesions.

Statistical tests

The Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman's correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and β; Dm, α, β, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs.

Results

Significant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P<0.001), high-grade PCa, and low-grade PCa (α:P=0.024, Dm:P=0.021). GG is correlated with certain CTRW parameters and ADC(α:P<0.001,r=-0.795; Dm:P<0.001,r=-0.762;ADC:P<0.001,r=-0.790). Moreover, CTRW parameters (α, β, Dm) combined with ADC showed the best diagnostic efficacy for distinguishing between PCa and CP as well as predicting Gleason grading. The differences among AUCs of ADC, CTRW parameters and their combinations were not statistically significant (P=0.051-0.526).

Conclusion

CTRW parameters α and Dm, as well as their combination were beneficial to distinguish between CA and PCa, low-grade PCa and high-grade PCa lesions, and CTRW parameters and ADC had comparable diagnostic 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.

High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue

Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: 'pseudo-diploid' cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.

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

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

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.

Prognostic Significance of the Cribriform Pattern in Prostate Cancer: Clinical Outcomes and Genomic Alterations

PURPOSE

Given the diverse clinical progression of prostate cancer (PC) and the evolving significance of histopathological factors in its management, this study aimed to explore the impact of cribriform pattern 4 (CP4) on clinical outcomes in PC patients and examine its molecular characteristics.

METHODS

This retrospective study analyzed data from The Cancer Genome Atlas (TCGA) database and included PC patients who underwent radical prostatectomy (RP) and had pathology slides available for the assessment of CP4. A multivariable competing risk regression analysis was used to assess the association between CP4 and progression-free survival (PFS) while adjusting for established PC prognostic factors. The frequency of genomic alterations was compared between patients with and without CP4 using the Fisher's exact test.

RESULTS

Among the 394 patients analyzed, 129 (32.74%) had CP4. After a median follow-up of 40.50 months (IQR: 23.90, 65.60), the presence of CP4 was significantly associated with lower PFS (AHR, 1.84; 95% CI, 1.08 to 3.114; p = 0.023) after adjusting for covariates. Seven hub genes-KRT13, KRT5, KRT15, COL17A1, KRT14, KRT16, and TP63-had significantly lower mRNA expression levels in patients with CP4 compared to those without.

CONCLUSIONS

PC patients with CP4 have distinct genomic alterations and are at a high risk of disease progression following RP. Therefore, these patients may benefit from additional post-RP treatments and should be the subject of a prospective randomized clinical trial.

A phase IIb randomized placebo-controlled trial testing the effect of MAG-EPA long-chain omega-3 fatty acid dietary supplement on prostate cancer proliferation

BACKGROUND

High prostate eicosapentaenoic fatty acid (EPA) levels were associated with a significant reduction of upgrading to grade group (GG) ≥ 2 prostate cancer in men under active surveillance. We aimed to evaluate the effect of MAG-EPA long-chain omega-3 fatty acid dietary supplement on prostate cancer proliferation.

METHODS

A phase II double-blind randomized placebo-controlled trial was conducted in 130 men diagnosed with GG ≥ 2 prostate cancer and undergoing radical prostatectomy between 2015-2017 (Clinicaltrials.gov: NCT02333435). Participants were randomized to receive 3 g daily of either MAG-EPA (n = 65) or placebo (n = 65) for 7 weeks (range 4-10) prior to radical prostatectomy. The primary outcome was the cancer proliferation index quantified by automated image analysis of tumor nuclear Ki-67 expression using standardized prostatectomy tissue microarrays. Additional planned outcomes at surgery are reported including plasma levels of 27 inflammatory cytokines and fatty acid profiles in circulating red blood cells membranes and prostate tissue.

RESULTS

Cancer proliferation index measured by Ki-67 expression was not statistically different between the intervention (3.10%) and placebo (2.85%) groups (p = 0.64). In the per protocol analyses, the adjusted estimated effect of MAG-EPA was greater but remained non-significant. Secondary outcome was the changes in plasma levels of 27 cytokines, of which only IL-7 was higher in MAG-EPA group compared to placebo (p = 0.026). Men randomized to MAG-EPA prior to surgery had four-fold higher EPA levels in prostate tissue compared to those on placebo.

CONCLUSIONS

This MAG-EPA intervention did not affect the primary outcome of prostate cancer proliferation according to nuclear Ki-67 expression. More studies are needed to decipher the effects of long-chain omega-3 fatty acid dietary supplementation in men with prostate cancer.

PI-RADS v2.1 and PSAD for the prediction of clinically significant prostate cancer among patients with PSA levels of 4-10 ng/ml

This study intended to evaluate the diagnostic accuracy of the prostate imaging reporting and data system (PI-RADS) and prostate-specific antigen density (PSAD) for clinically significant prostate cancer (csPCa) with PSA levels of 4-10 ng/ml. Between July 2018 and June 2022, a total of 453 patients with PSA levels of 4-10 ng/ml were retrospectively included, which were randomly assigned to the training group (323 patients) and validation group (130 patients). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with their 95% CI were calculated. The overall diagnostic performance was determined with area under the receiver operating characteristic curve (AUC), and an integrated nomogram combining PI-RADS score and PSAD was constructed and tested in a validation cohort. In the training group, the AUC for PI-RADS 2.1 and PSAD alone were 0.875 (95% CI 0.834-0.916) and 0.712 (95% CI 0.648-0.775). At the cutoff PI-RADS score ≥ 4, the sensitivity and specificity were 86.2% (95% CI 77.4-1.9%) and 84.7% (95% CI 79.6-88.8%), respectively. For PSAD, the sensitivity and specificity were 73.3% (95% CI 63.0-82.4%) and 62.1% (95% CI 55.8-68.5%) at the cutoff 0.162 ng/ml/ml. While combining PI-RADS with PSAD, the diagnostic performance was improved significantly, with AUC of 0.893 (95% CI 0.853-0.933). In the validation group, the nomogram yielded a AUC of 0.871 (95% CI 0.807-0.934), which is significantly higher than PI-RADS alone (0.829, 95% CI 0.759-0.899, P = 0.02). For patients with PSA levels of 4-10 ng/ml, PSAD demonstrated moderate diagnostic accuracy whereas PI-RADS showed high performance. By combination of PSAD and PI-RADS together, the diagnostic performance could be improved significantly.

Inhibition of the Cyclin K-CDK12 complex induces DNA damage and increases the effect of androgen deprivation therapy in prostate cancer

Androgen deprivation therapy (ADT) is the mainstay of the current first-line treatment concepts for patients with advanced prostate carcinoma (PCa). However, due to treatment failure and recurrence investigation of new targeted therapeutics is urgently needed. In this study, we investigated the suitability of the Cyclin K-CDK12 complex as a novel therapeutic approach in PCa using the new covalent CDK12/13 inhibitor THZ531. Here we show that THZ531 impairs cellular proliferation, induces apoptosis, and decreases the expression of selected DNA repair genes in PCa cell lines, which is associated with an increasing extent of DNA damage. Furthermore, combination of THZ531 and ADT leads to an increase in these anti-tumoral effects in androgen-sensitive PCa cells. The anti-proliferative and pro-apoptotic activity of THZ531 in combination with ADT was validated in an ex vivo PCa tissue culture model. In a retrospective immunohistochemical analysis of 300 clinical tissue samples we show that Cyclin K (CycK) but not CDK12 expression correlates with a more aggressive type of PCa. In conclusion, this study demonstrates the clinical relevance of the CycK-CDK12 complex as a promising target for combinational therapy with ADT in PCa and its importance as a prognostic biomarker for patients with PCa.

Prostate cancer: Molecular aspects, consequences, and opportunities of the multifocal nature

Prostate cancer is unique compared to other major cancers due to the presence of multiple primary malignant foci in the majority of patients at the time of diagnosis. Each malignant focus has distinct somatic mutations and gene expression patterns, which represents a challenge for the development of prognostic tests for localized prostate cancer. Additionally, the molecular heterogeneity of advanced prostate cancer has important implications for management, particularly for patients with metastatic and locally recurrent cancer. Studies have shown that prostate cancers with mutations in DNA damage response genes are more sensitive to drugs inhibiting the poly ADP-ribose polymerase (PARP) enzyme. However, testing for such mutations should consider both spatial and temporal heterogeneity. Here, we summarize studies where multiregional genomics and transcriptomics analyses have been performed for primary prostate cancer. We further discuss the vast interfocal heterogeneity and how prognostic biomarkers and a molecular definition of the index tumor should be developed. The concept of focal treatments in prostate cancer has been evolving as a demand from patients and clinicians and is one example where there is a need for defining an index tumor. Here, biomarkers must have proven value for individual malignant foci. The potential discovery and implementation of biomarkers that are agnostic to heterogeneity are also explored as an alternative to multisample testing. Thus, deciding upon whole-organ treatment, such as radical prostatectomy, should depend on information from biomarkers which are informative for the whole organ.

Values of multiparametric and biparametric MRI in diagnosing clinically significant prostate cancer: a multivariate analysis

BACKGROUND

To investigate the value of semi-quantitative and quantitative parameters (PI-RADS score, T2WI score, ADC, Ktrans, and Kep) based on multiparametric MRI (mpMRI) or biparametric MRI (bpMRI) combined with prostate specific antigen density (PSAD) in detecting clinically significant prostate cancer (csPCa).

METHODS

A total of 561 patients (276 with csPCa; 285 with non-csPCa) with biopsy-confirmed prostate diseases who underwent preoperative mpMRI were included. Prostate volume was measured for calculation of PSAD. Prostate index lesions were scored on a five-point scale on T2WI images (T2WI score) and mpMRI images (PI-RADS score) according to the PI-RADS v2.1 scoring standard. DWI and DCE-MRI images were processed to measure the quantitative parameters of the index lesion, including ADC, Kep, and Ktrans values. The predictors of csPCa were screened by logistics regression analysis. Predictive models of bpMRI and mpMRI were established. ROC curves were used to evaluate the efficacy of parameters and the model in diagnosing csPCa.

RESULTS

The independent diagnostic accuracy of PSA density, PI-RADS score, T2WI score, ADCrec, Ktrans, and Kep for csPCa were 80.2%, 89.5%, 88.3%, 84.6%, 58.5% and 61.6%, respectively. The diagnostic accuracy of bpMRI T2WI score and ADC value combined with PSAD was higher than that of PI-RADS score. The combination of mpMRI PI‑RADS score, ADC value with PSAD had the highest diagnostic accuracy.

CONCLUSIONS

PI-RADS score according to the PI-RADS v2.1 scoring standard was the most accurate independent diagnostic index. The predictive value of bpMRI model for csPCa was slightly lower than that of mpMRI model, but higher than that of PI-RADS score.

Head-to-head: how many categories for grading urothelial carcinoma?

Tumour grade is a critical prognostic parameter for guiding the management of patients with non-muscle invasive bladder cancer. In 2004, the World Health Organisation (WHO) adopted a binary (low-grade/high-grade) grading system to replace the three-tier (grades 1-3) system used to grade urothelial carcinoma since 1973. However, there is significant global variation in the grading of urothelial carcinoma. Some pathology and clinical guidelines recommend reporting of the WHO 1973 and 2004 grades in parallel, while others require reporting only of the WHO 2004 grade. This variation in pathology practice is clinically significant, because the two grading systems are not readily translatable. Some experts have proposed novel systems for grading urothelial carcinoma that involve splitting of the WHO 1973 and 2004 grade categories. The arguments for and against splitting urothelial carcinomas into two-, three- and four-grade categories are independently discussed by the three authors.

Oncological outcomes of cribriform histology pattern in prostate cancer patients: a systematic review and meta-analysis

BACKGROUND

Changes applied to the Prostate cancer (PCa) histopathology grading, where patients with cribriform patterns (CP) may be categorized as grade group 2 and could hypothetically be surveilled. However, CP has been associated with worse oncological outcomes. The aim of our study is to systematically review and meta-analyze the available evidence on CP in PCa patients.

METHODS

This analysis was registered on PROSPERO (CRD42022298473). We performed a systematic literature search of PubMed, EMBASE and Scopus using Medical Subject Headings (MeSH) indexes, keyword searches, and publication types until December 2021. The search terms included: "prostate", "prostate cancer" and "cribriform". We also searched reference lists of relevant articles. Eligible studies included published journal articles that provided quantitative data on the association between cribriform patterns at radical prostatectomy and the presence of extra-prostatic extension (EPE), seminal vesicle invasion (SVI), positive surgical margins (PSM), biochemical recurrence (BCR) or cancer specific mortality (CSM).

RESULTS

Overall, 31 studies were included for the quantitative analysis. All articles have been published during a span of 11 years (2011-2022) with a mean month of follow-up of 62.87 months. The mean quality of these studies, assessed with the Newcastle Ottawa Scale was 6.27. We demonstrated that CP was associated with greater risk of EPE (odds ratio [OR] 1.96; P < 0.0001), SVI (OR: 2.89; p < 0.01), and PSM (OR: 1.88; p < 0.0007). Our analyses showed that CP was associated with greater risk of BCR (hazard ratio [HR]: 2.14; p < 0.01) and of CSM (HR: 3.30, p < 0.01).

CONCLUSION

The presence of CP is associated with adverse pathology at radical prostatectomy and worse biochemical recurrence and cancer specific mortality. These results highlight the importance of a better pathologic report of CP to advise clinician for a strict follow-up in PCa patients.

Is prostatic adenocarcinoma with cribriform architecture more difficult to detect on prostate MRI?

BACKGROUND

Cribriform (CBFM) pattern on prostate biopsy has been implicated as a predictor for high-risk features, potentially leading to adverse outcomes after definitive treatment. This study aims to investigate whether the CBFM pattern containing prostate cancers (PCa) were associated with false negative magnetic resonance imaging (MRI) and determine the association between MRI and histopathological disease burden.

METHODS

Patients who underwent multiparametric magnetic resonance imaging (mpMRI), combined 12-core transrectal ultrasound (TRUS) guided systematic (SB) and MRI/US fusion-guided biopsy were retrospectively queried for the presence of CBFM pattern at biopsy. Biopsy cores and lesions were categorized as follows: C0 = benign, C1 = PCa with no CBFM pattern, C2 = PCa with CBFM pattern. Correlation between cancer core length (CCL) and measured MRI lesion dimension were assessed using a modified Pearson correlation test for clustered data. Differences between the biopsy core groups were assessed with the Wilcoxon-signed rank test with clustering.

RESULTS

Between 2015 and 2022, a total of 131 consecutive patients with CBFM pattern on prostate biopsy and pre-biopsy mpMRI were included. Clinical feature analysis included 1572 systematic biopsy cores (1149 C0, 272 C1, 151 C2) and 736 MRI-targeted biopsy cores (253 C0, 272 C1, 211 C2). Of the 131 patients with confirmed CBFM pathology, targeted biopsy (TBx) alone identified CBFM in 76.3% (100/131) of patients and detected PCa in 97.7% (128/131) patients. SBx biopsy alone detected CBFM in 61.1% (80/131) of patients and PCa in 90.8% (119/131) patients. TBx and SBx had equivalent detection in patients with smaller prostates (p = 0.045). For both PCa lesion groups there was a positive and significant correlation between maximum MRI lesion dimension and CCL (C1 lesions: p < 0.01, C2 lesions: p < 0.001). There was a significant difference in CCL between C1 and C2 lesions for T2 scores of 3 and 5 (p ≤ 0.01, p ≤ 0.01, respectively) and PI-RADS 5 lesions (p ≤ 0.01), with C2 lesions having larger CCL, despite no significant difference in MRI lesion dimension.

CONCLUSIONS

The extent of disease for CBFM-containing tumors is difficult to capture on mpMRI. When comparing MRI lesions of similar dimensions and PIRADS scores, CBFM-containing tumors appear to have larger cancer yield on biopsy. Proper staging and planning of therapeutic interventions is reliant on accurate mpMRI estimation. Special considerations should be taken for patients with CBFM pattern on prostate biopsy.

Quantitative Evaluation of Apparent Diffusion Coefficient Values, ISUP Grades and Prostate-Specific Antigen Density Values of Potentially Malignant PI-RADS Lesions

The aim of this study was to demonstrate the correlation between ADC values and the ADC/PSAD ratio for potentially malignant prostate lesions classified into ISUP grades and to determine threshold values to differentiate benign lesions (noPCa), clinically insignificant (nsPCa) and clinically significant prostate cancer (csPCa). We enrolled a total of 403 patients with 468 prostate lesions, of which 46 patients with 50 lesions were excluded for different reasons. Therefore, 357 patients with a total of 418 prostate lesions remained for the final evaluation. For all lesions, ADC values were measured; they demonstrated a negative correlation with ISUP grades (p < 0.001), with a significant difference between csPCa and a combined group of nsPCa and noPCa (ns-noPCa, p < 0.001). The same was true for the ADC/PSAD ratio, but only the ADC/PSAD ratio proved to be a significant discriminator between nsPCa and noPCa (p = 0.0051). Using the calculated threshold values, up to 31.6% of biopsies could have been avoided. Furthermore, the ADC/PSAD ratio, with the ability to distinguish between nsPCa and noPCa, offers possible active surveillance without prior biopsy.

A urine extracellular vesicle lncRNA classifier for high-grade prostate cancer and increased risk of progression: A multi-center study

To construct a urine extracellular vesicle long non-coding RNA (lncRNA) classifier that can detect high-grade prostate cancer (PCa) of grade group 2 or greater and estimate the risk of progression during active surveillance, we identify high-grade PCa-specific lncRNAs by combined analyses of cohorts from TAHSY, TCGA, and the GEO database. We develop and validate a 3-lncRNA diagnostic model (Clnc, being made of AC015987.1, CTD-2589M5.4, RP11-363E6.3) that can detect high-grade PCa. Clnc shows higher accuracy than prostate cancer antigen 3 (PCA3), multiparametric magnetic resonance imaging (mpMRI), and two risk calculators (Prostate Cancer Prevention Trial [PCPT]-RC 2.0 and European Randomized Study of Screening for Prostate Cancer [ERSPC]-RC) in the training cohort (n = 350), two independent cohorts (n = 232; n = 251), and TCGA cohort (n = 499). In the prospective active surveillance cohort (n = 182), Clnc at diagnosis remains a powerful independent predictor for overall active surveillance progression. Thus, Clnc is a potential biomarker for high-grade PCa and can also serve as a biomarker for improved selection of candidates for active surveillance.

Exploration of the diagnostic capacity of PSAMR combined with PI-RADS scoring for clinically significant prostate cancer and establishment and validation of the Nomogram prediction model

PURPOSE

The objective of this investigation was to explore the diagnostic capability of Prostate Specific Antigen Mass Ratio (PSAMR) combined with Prostate Imaging Reporting and Data System (PI-RADS) scoring for clinically significant prostate cancer (CSPC), develop and validate a Nomogram prediction model for the probability of prostate cancer occurrence in patients who have not undergone prostate biopsy.

METHODS

Initially, we retrospectively collected clinical and pathological data of patients who underwent trans-perineal prostate puncture at Yijishan Hospital of Wanan Medical College from July 2021 to January 2023. Through logistic univariate and multivariate regression analysis, independent risk factors for CSPC were determined. Receiver Operating Characteristic (ROC) curves were generated to compare the ability of different factors for diagnosis of CSPC. Then, we split the dataset into a training set and validation set, compared their heterogeneity, and developed a Nomogram prediction model based on the training set. Finally, we validated the Nomogram prediction model in terms of discrimination, calibration, and clinical usefulness.

RESULTS

Logistic multivariate regression analysis illustrated that age [64-69 (OR = 2.736, P = 0.029); 69-75 (OR = 4.728, P = 0.001); > 75 (OR = 11.344, P < 0.001)], PSAMR [0.44-0.73 (OR = 4.144, P = 0.028); 0.73-1.64(OR = 13.022, P < 0.001); > 1.64(OR = 50.541, P < 0.001)], and PI-RADS score [4 points (OR = 7.780, P < 0.001); 5 points (OR = 24.533, P < 0.001)] were independent risk factors for CSPC. The Area Under the Curve (AUC) of the ROC curves of PSA, PSAMR, PI-RADS score, and PSAMR combined with PI-RADS score were respectively 0.797, 0.874, 0.889, and 0.928. The performance of PSAMR and PI-RADS score for diagnosis of CSPC was superior to PSA, but inferior to PSAMR combined with PI-RADS. Age, PSAMR, and PI-RADS were included in the Nomogram prediction model. The AUCs of the training set ROC curve and the validation set ROC curve were 0.943 (95% CI 0.917-0.970) and 0.878 (95% CI 0.816-0.940), respectively, in the discrimination validation. The calibration curve showed good consistency, and the decision analysis curve suggested the model had good clinical efficacy.

CONCLUSIONS

We found that PSAMR combined with PI-RADS scoring had a strong diagnostic capability for CSPC, and provided a Nomogram prediction model to predict the probability of prostate cancer occurrence combined with clinical data.

Outcomes of a Diagnostic Pathway for Prostate Cancer Based on Biparametric MRI and MRI-Targeted Biopsy Only in a Large Teaching Hospital

BACKGROUND

Diagnostic pathways for prostate cancer (PCa) balance detection rates and burden. MRI impacts biopsy indication and strategy.

METHODS

A prospectively collected cohort database (N = 496) of men referred for elevated PSA and/or abnormal DRE was analyzed. All underwent biparametric MRI (3 Tesla scanner) and ERSPC prostate risk-calculator. Indication for biopsy was PIRADS ≥ 3 or risk-calculator ≥ 20%. Both targeted (cognitive-fusion) and systematic cores were combined. A hypothetical full-MRI-based pathway was retrospectively studied, omitting systematic biopsies in: (1) PIRADS 1-2 but risk-calculator ≥ 20%, (2) PIRADS ≥ 3, receiving targeted biopsy-cores only.

RESULTS

Significant PCa (GG ≥ 2) was detected in 120 (24%) men. Omission of systematic cores in cases with PIRADS 1-2 but risk-calculator ≥ 20%, would result in 34% less biopsy indication, not-detecting 7% significant tumors. Omission of systematic cores in PIRADS ≥ 3, only performing targeted biopsies, would result in a decrease of 75% cores per procedure, not detecting 9% significant tumors. Diagnosis of insignificant PCa dropped by 52%. PCa undetected by targeted cores only, were ipsilateral to MRI-index lesions in 67%.

CONCLUSIONS

A biparametric MRI-guided PCa diagnostic pathway would have missed one out of six cases with significant PCa, but would have considerably reduced the number of biopsy procedures, cores, and insignificant PCa. Further refinement or follow-up may identify initially undetected cases. Center-specific data on the performance of the diagnostic pathway is required.

The Prognostic Significance of Selected HLA Alleles on Prostate Cancer Outcome

Recently, we have shown that HLA-A*02:01 and HLA-A*24:02 in de novo metastatic prostate cancer (MPCa) have an important role in disease progression. Since de novo MPCa represents a small group among patients diagnosed with prostate cancer (PCa), it was obvious to try to extend the validity of our results to larger cohorts of PCa patients. Herein, we analyzed patients irrespective of their disease status at diagnosis to include, besides patients with MPCa, those with localized PCa (LPCa). Our goal was to specify the prognostic value of HLA-A*02:01 and HLA-A*24:02 for overall survival (OS) prospectively and for early biochemical recurrence (BCR) and castrate resistance (CR) as additional clinical endpoints in a prospective/retrospective manner, to improve clinical decisions for patients covering all stages of PCa. On univariate analysis, HLA-A alleles were significantly associated as prognostic biomarkers with early BCR (p = 0.028; HR = 1.822), OS (p = 0.013; HR = 1.547) and showed a trend for CR (p = 0.150; HR = 1.239). On multivariate analysis, HLA-A alleles proved to be independent prognosticators for early BCR (p = 0.017; HR = 2.008), CR (p = 0.005; HR = 1.615), and OS (p = 0.002; HR = 2.063). Kaplan-Meier analyses revealed that patients belonging to the HLA-A*02:01+HLA-A*24:02- group progressed much faster to BCR and CR and had also shorter OS compared to HLA-A*24:02+ patients. Patients being HLA-A*02:01-HLA-A*24:02- exhibited varying clinical outcomes, pointing to the presence of additional HLA-A alleles with potential prognostic value. Our data underline the HLA-A alleles as valuable prognostic biomarkers for PCa that may assist with the appropriate treatment and follow-up schedule based on the risk for disease progression to avoid over-diagnosis and over-treatment.

Accelerating Cancer Histopathology Workflows with Chemical Imaging and Machine Learning

Histopathology has remained a cornerstone for biomedical tissue assessment for over a century, with a resource-intensive workflow involving biopsy or excision, gross examination, sampling, tissue processing to snap frozen or formalin-fixed paraffin-embedded blocks, sectioning, staining, optical imaging, and microscopic assessment. Emerging chemical imaging approaches, including stimulated Raman scattering (SRS) microscopy, can directly measure inherent molecular composition in tissue (thereby dispensing with the need for tissue processing, sectioning, and using dyes) and can use artificial intelligence (AI) algorithms to provide high-quality images. Here we show the integration of SRS microscopy in a pathology workflow to rapidly record chemical information from minimally processed fresh-frozen prostate tissue. Instead of using thin sections, we record data from intact thick tissues and use optical sectioning to generate images from multiple planes. We use a deep learning–based processing pipeline to generate virtual hematoxylin and eosin images. Next, we extend the computational method to generate archival-quality images in minutes, which are equivalent to those obtained from hours/days-long formalin-fixed, paraffin-embedded processing. We assessed the quality of images from the perspective of enabling pathologists to make decisions, demonstrating that the virtual stained image quality was diagnostically useful and the interpathologist agreement on prostate cancer grade was not impacted. Finally, because this method does not wash away lipids and small molecules, we assessed the utility of lipid chemical composition in determining grade. Together, the combination of chemical imaging and AI provides novel capabilities for rapid assessments in pathology by reducing the complexity and burden of current workflows.

SIGNIFICANCE

Archival-quality (formalin-fixed paraffin-embedded), thin-section diagnostic images are obtained from thick-cut, fresh-frozen prostate tissues without dyes or stains to expedite cancer histopathology by combining SRS microscopy and machine learning.

A nomogram based on biparametric magnetic resonance imaging for detection of clinically significant prostate cancer in biopsy-naïve patients

PURPOSE

This study aimed to develop and validate a model based on biparametric magnetic resonance imaging (bpMRI) for the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve patients.

METHOD

This retrospective study included 324 patients who underwent bpMRI and MRI targeted fusion biopsy (MRGB) and/or systematic biopsy, of them 217 were randomly assigned to the training group and 107 were assigned to the validation group. We assessed the diagnostic performance of three bpMRI-based scorings in terms of sensitivity and specificity. Subsequently, 3 models (Model 1, Model 2, and Model 3) combining bpMRI scorings with clinical variables were constructed and compared with each other using the area under the receiver operating characteristic (ROC) curves (AUC). The statistical significance of differences among these models was evaluated using DeLong's test.

RESULTS

In the training group, 68 of 217 patients had pathologically proven csPCa. The sensitivity and specificity for Scoring 1 were 64.7% (95% CI 52.2%-75.9%) and 80.5% (95% CI 73.3%-86.6%); for Scoring 2 were 86.8% (95% CI 76.4%-93.8%) and 73.2% (95% CI 65.3%-80.1%); and for Scoring 3 were 61.8% (95% CI 49.2%-73.3%) and 80.5% (95% CI 73.3%-86.6%), respectively. Multivariable regression analysis revealed that scorings based on bpMRI, age, and prostate-specific antigen density (PSAD) were independent predictors of csPCa. The AUCs for the 3 models were 0.88 (95% CI 0.83-0.93), 0.90 (95% CI 0.85-0.94), and 0.88 (95% CI 0.83-0.93), respectively. Model 2 showed significantly higher performance than Model 1 (P = 0.03) and Model 3 (P < 0.01).

CONCLUSION

All three scorings had favorite diagnostic accuracy. While in conjunction with age and PSAD the prediction power was significantly improved, and the Model 2 that based on Scoring 2 yielded the highest performance.

Comparative impact of grade on mortality across salivary cancers: A novel, unifying staging system

BACKGROUND

The comparative impact of histologic variants and grade has not been well described.

METHODS

Salivary cancer histologies were profiled using hospital and population-based cancer registries. Multivariable models were employed to assess relationships between histology, grade, and survival.

RESULTS

On univariate analysis, histologic variants exhibited a wide spectrum of mortality risk (5-year overall survival (OS): 86% (acinic cell carcinoma), 78% (mucoepidermoid carcinoma), 72% (adenoid cystic carcinoma), 64% (carcinoma ex-pleomorphic adenoma), 52% (adenocarcinoma NOS), and 47% (salivary duct carcinoma) (p < 0.001). However, on multivariable analysis these differences largely vanished. Worsening grade corresponded with deteriorating survival (5-year OS: 89% [low-grade], 81% [intermediate-grade], 45% [high-grade]; p < 0.001), which was upheld on multivariable analysis and propensity score matching. Recursive partitioning analysis generated TNM + G schema (c-index 0.75) superior to the existing system (c-index 0.73).

CONCLUSION

Grade represents a primary determinant of salivary cancer prognosis. Integrating grade into stage strengthens current staging systems.

The Impact of Multiparametric Magnetic Resonance Imaging on Treatment Strategies for Incidental Prostate Cancer after Holmium Laser Enucleation of the Prostate

PURPOSE

To investigate the impact of multiparametric magnetic resonance imaging (mpMRI) on treatment strategies for incidental prostate cancer (iPCa) after holmium enucleation of the prostate (HoLEP); Methods: Data from 1781 men who underwent HoLEP for clinical bladder outlet obstruction between September 2009 and March 2022 were reviewed retrospectively. Among patients with confirmed iPCa, those with prostate-specific antigen (PSA) levels < 10 ng/mL and who underwent mpMRI 3 months after HoLEP were included. Pathologic results, including Gleason grade (GG) and tumor volume, were identified. mpMRI was interpreted using the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2). Treatment strategies for iPCa according to GG alone, or according to a combination of Gleason grade and mpMRI, were analyzed and compared.

RESULTS

Of 1764 men with serum PSA levels < 10 ng/mL, iPCa was confirmed in 64 (3.6%) after HoLEP. Of the 62 men who underwent mpMRI, the median (IQR) age at the time of HoLEP was 72.5 (66.5-78.0) years. The median PSA level and prostate volume were 3.49 (1.82-5.03) ng/mL and 49.6 (38.5-85.4) cm³, respectively. The pathologic results of iPCa were as follows: GG1 = 42 (67.7%), GG2 = 13 (21.0%), GG3 = 2 (3.2%), GG4 = 1 (1.6%), and GG5 = 4 (6.5%). Of the patients with GG1 and GG2, 78.6% (33/42) and 53.8% (7/13), respectively, underwent active surveillance (AS). However, of 42 patients with GG1, 27 (64.3%) had a PI-RADSv2 score of 2, and 24 (88.9%) of them underwent AS. Of the 13 patients with GG2, 4 (80%) with a PI-RADSv2 score of 2 underwent AS. All patients with GG 3-5 were clinically expected to have locally advanced PCa and be treated with radiotherapy and/or ADT.

CONCLUSIONS

For patients with iPCa of GG 1-2 after HoLEP, mpMRI helps to establish a treatment strategy by allowing risk stratification to select those who should be considered for AS or active treatment.

Critical Evaluation of Transcripts and Long Noncoding RNA Expression Levels in Prostate Cancer Following Radical Prostatectomy

INTRODUCTION

The clinical course of prostate cancer (PCa) is highly variable, ranging from indolent behavior to rapid metastatic progression. The Gleason score is widely accepted as the primary histologic assessment tool with significant prognostic value. However, additional biomarkers are required to better stratify patients, particularly those at intermediate risk.

METHODS

In this study, we analyzed the expression of 86 cancer hallmark genes in 171 patients with PCa who underwent radical prostatectomy and focused on the outcome of the 137 patients with postoperative R0-PSA0 status.

RESULTS

Low expression of the IGF1 and SRD52A, and high expression of TIMP2, PLAUR, S100A2, and CANX genes were associated with biochemical recurrence (BR), defined as an increase of prostate-specific antigen above 0.2 ng/mL. Furthermore, the analysis of the expression of 462 noncoding RNAs (ncRNA) in a sub-cohort of 39 patients with Gleason score 7 tumors revealed that high levels of expression of the ncRNAs LINC00624, LINC00593, LINC00482, and cd27-AS1 were significantly associated with BR. Our findings provide further evidence for tumor-promoting roles of ncRNAs in PCa patients at intermediate risk. The strong correlation between expression of LINC00624 and KRT8 gene, encoding a well-known cell surface protein present in PCa, further supports a potential contribution of this ncRNA to PCa progression.

CONCLUSION

While larger and further studies are needed to define the role of these genes/ncRNA in PCa, our findings pave the way toward the identification of a subgroup of patients at intermediate risk who may benefit from adjuvant treatments and new therapeutic agents.

Multimodal convolutional neural networks based on the Raman spectra of serum and clinical features for the early diagnosis of prostate cancer

We collected surface-enhanced Raman spectroscopy (SERS) data from the serum of 729 patients with prostate cancer or benign prostatic hyperplasia (BPH), corresponding to their pathological results, and built an artificial intelligence-assisted diagnosis model based on a convolutional neural network (CNN). We then evaluated its value in diagnosing prostate cancer and predicting the Gleason score (GS) using a simple cross-validation method. Our CNN model based on the spectral data for prostate cancer diagnosis revealed an accuracy of 85.14 ± 0.39%. After adjusting the model with patient age and prostate specific antigen (PSA), the accuracy of the multimodal CNN was up to 88.55 ± 0.66%. Our multimodal CNN for distinguishing low-GS/high-GS and GS = 3 + 3/GS = 3 + 4 revealed accuracies of 68 ± 0.58% and 77 ± 0.52%, respectively.

Research of Prostate Cancer Urinary Diagnostic Biomarkers by Proteomics: The Noteworthy Influence of Inflammation

Nowadays, in the case of suspected prostate cancer (PCa), tissue needle biopsy remains the benchmark for diagnosis despite its invasiveness and poor tolerability, as serum prostate-specific antigen (PSA) is limited by low specificity. The aim of this proteomic study was to identify new diagnostic biomarkers in urine, an easily and non-invasively available sample, able to selectively discriminate cancer from benign prostatic hyperplasia (BPH), evaluating whether the presence of inflammation may be a confounding parameter. The analysis was performed by two-dimensional gel electrophoresis (2-DE), mass spectrometry (LC-MS/MS) and Enzyme-Linked Immunosorbent Assay (ELISA) on urine samples from PCa and BPH patients, divided into subgroups based on the presence or absence of inflammation. Significant quantitative and qualitative differences were found in the urinary proteomic profile of PCa and BPH groups. Of the nine differentially expressed proteins, only five can properly be considered potential biomarkers of PCa able to discriminate the two diseases, as they were not affected by the inflammatory process. Therefore, the proteomic research of novel and reliable urinary biomarkers of PCa should be conducted considering the presence of inflammation as a realistic interfering element, as it could hinder the detection of important protein targets.

Prostate Adenocarcinoma Grade Group 1: Rationale for Retaining a Cancer Label in the 2022 World Health Organization Classification

We present the rationale for keeping the "cancer" label for grade group 1 (GG1) prostate cancer. Maintaining GG1 as the lowest grade outweighs the potential benefits that a benign designation may bring. Patient and surgeon education on the vital role of active surveillance for GG1 cancers and avoidance of overtreatment should be the focus rather than such a drastic change in nomenclature.

PSA reactivity in extracellular microvesicles to commercial immunoassays

AIMS

Characterization of PSA in extracellular microvesicles (EVs) and its reactivity to commercial methods.

MATERIALS AND METHODS

EVs derived from serum of 47 prostate cancer (PCa) patients, 27 benign prostatic hyperplasia (BPH) patients and 42 healthy controls were analyzed. EVs isolation and quantification of PSA immunoreactive to total (ev-T-PSA) or free (ev-F-PSA) PSA immunoassays, were performed using commercial assays. PSA in CD81+ or CD63+ EVs was determined directly in serum by an immunocapture-ELISA (IC-ELISA).

RESULTS

Ev-T-PSA immunoreactive to Elecsys assay was detected in all samples. Median T-PSA ev/srm ratio was 2.20% (Q1-Q3: 0.80-4.00%), although in some samples this ratio reached 59%. T-PSA ev/srm ratio was higher in those samples with serum T-PSA below 4 µg/L than in those exceeding that cut-off (p<0.001). T-PSA ev/srm ratio was lower in PCa patients compared to healthy controls and BPH patients (p<0.001). Elecsys immunoassays detected higher concentrations of ev-T-PSA and ev-F-PSA than Immulite (p<0.001). PSA was detected by IC-ELISA more intensely in CD81+ EVs than in CD63+ EVs, and ev-T-PSA correlated with PSA+CD63+ (p<0.001) but not with PSA+CD81+.

CONCLUSION

EVs-bound PSA is another form of circulating PSA whose measurement could be easily performed in clinical laboratories by automated immunoassays.

Vitamin D and genetic ancestry are associated with apoptosis rates in benign and malignant prostatic epithelium

PURPOSE

Vitamin D metabolites may be protective against prostate cancer (PCa). We conducted a cross-sectional analysis to evaluate associations between in vivo vitamin D status, genetic ancestry, and degree of apoptosis using prostatic epithelial terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining.

EXPERIMENTAL DESIGN

Benign and tumor epithelial punch biopsies of participants with clinically localized PCa underwent indirect TUNEL staining. Serum levels of 25 hydroxyvitamin D [25(OH)D] and 1,25 dihydroxyvitamin D were assessed immediately before radical prostatectomy; levels of prostatic 25(OH)D were obtained from the specimen once the prostate was extracted. Ancestry informative markers were used to estimate the percentage of genetic West African, Native American, and European ancestry.

RESULTS

One hundred twenty-one newly diagnosed men, age 40-79, were enrolled between 2013 and 2018. Serum 25(OH)D correlated positively with both tumor (ρ = 0.17, p = 0.03), and benign (ρ = 0.16, p = 0.04) prostatic epithelial TUNEL staining. Similarly, prostatic 25(OH)D correlated positively with both tumor (ρ = 0.31, p < 0.001) and benign (ρ = 0.20, p = 0.03) epithelial TUNEL staining. Only Native American ancestry was positively correlated with tumor (ρ = 0.22, p = 0.05) and benign (ρ = 0.27, p = 0.02) TUNEL staining. In multivariate regression models, increasing quartiles of prostatic 25(OH)D (β = 0.25, p = 0.04) and Native American ancestry (β = 0.327, p = 0.004) were independently associated with tumor TUNEL staining.

CONCLUSIONS

Physiologic serum and prostatic 25(OH)D levels and Native American ancestry are positively associated with the degree of apoptosis in tumor and benign prostatic epithelium in clinically localized PCa. Vitamin D may have secondary chemoprevention benefits in preventing PCa progression in localized disease.

Effects of dynamic contrast enhancement on transition zone prostate cancer in Prostate Imaging Reporting and Data System Version 2.1

BACKGROUND

The aim of the study was to analyse the effects of dynamic contrast enhanced (DCE)-MRI on transitional-zone prostate cancer (tzPCa) and clinically significant transitional-zone prostate cancer (cs-tzPCa) in Prostate Imaging Reporting and Data System (PI-RADS) Version 2.1.

PATIENTS AND METHODS

The diagnostic efficiencies of T2-weighted imaging (T2WI) + diffusion-weighted imaging (DWI), T2WI + dynamic contrast-enhancement (DCE), and T2WI + DWI + DCE in tzPCa and cs-tzPCa were compared using the score of ≥ 4 as the positive threshold and prostate biopsy as the reference standard.

RESULTS

A total of 425 prostate cases were included in the study: 203 cases in the tzPCa group, and 146 in the cs-tzPCa group. The three sequence combinations had the similar areas under the curves in diagnosing tzPCa and cs-tzPCa (all P < 0.05). The sensitivity of T2WI + DCE and T2WI + DWI + DCE (84.7% and 85.7% for tzPCa; 88.4% and 89.7% for cs-tzPCa, respectively) in diagnosing tzPCa and cs-tzPCa was significantly greater than that of T2WI + DWI (79.3% for tzPCa; 82.9% for cs-tzPCa). The specificity of T2WI + DWI (86.5% for tzPCa; 74.9% for cs-tzPCa) were significantly greater than those of T2WI + DCE and T2WI + DWI + DCE (68.0% and 68.5% for tzPCa; 59.1% and 59.5% for cs-tzPCa, respectively) (all P > 0.05). The diagnostic efficacies of T2WI + DCE and T2WI + DWI + DCE had no significant differences (all P < 0.05).

CONCLUSIONS

DCE can improve the sensitivity of diagnosis for tzPCa and cs-tzPCa, and it is useful for small PCa lesion diagnosis.

Sub-differentiation of PI-RADS 3 lesions in TZ by advanced diffusion-weighted imaging to aid the biopsy decision process

Background

Performing biopsy for intermediate lesions with PI-RADS 3 has always been controversial. Moreover, it is difficult to differentiate prostate cancer (PCa) and benign prostatic hyperplasia (BPH) nodules in PI-RADS 3 lesions by conventional scans, especially for transition zone (TZ) lesions. The purpose of this study is sub-differentiation of transition zone (TZ) PI-RADS 3 lesions using intravoxel incoherent motion (IVIM), stretched exponential model, and diffusion kurtosis imaging (DKI) to aid the biopsy decision process.

Methods

A total of 198 TZ PI-RADS 3 lesions were included. 149 lesions were BPH, while 49 lesions were PCa, including 37 non-clinical significant PCa (non-csPCa) lesions and 12 clinical significant PCa (csPCa) lesions. Binary logistic regression analysis was used to examine which parameters could predict PCa in TZ PI-RADS 3 lesions. The ROC curve was used to test diagnostic efficiency in distinguishing PCa from TZ PI-RADS 3 lesions, while one-way ANOVA analysis was used to examine which parameters were statistically significant among BPH, non-csPCa and csPCa.

Results

The logistic model was statistically significant (χ2 = 181.410, p<0.001) and could correctly classify 89.39% of the subjects. Parameters of fractional anisotropy (FA) (p=0.004), mean diffusion (MD) (p=0.005), mean kurtosis (MK) (p=0.015), diffusion coefficient (D) (p=0.001), and distribute diffusion coefficient (DDC) (p=0.038) were statistically significant in the model. ROC analysis showed that AUC was 0.9197 (CI 95%: 0.8736-0.9659). Sensitivity, specificity, positive predictive value and negative predictive value were 92.1%, 80.4%, 93.9% and 75.5%, respectively. FA and MK of csPCa were higher than those of non-csPCa (all p<0.05), while MD, ADC, D, and DDC of csPCa were lower than those of non-csPCa (all p<0.05).

Conclusion

FA, MD, MK, D, and DDC can predict PCa in TZ PI-RADS 3 lesions and inform the decision-making process of whether or not to perform a biopsy. Moreover, FA, MD, MK, D, DDC, and ADC may have ability to identify csPCa and non-csPCa in TZ PI-RADS 3 lesions.

Variation in patient reported outcomes following radical prostatectomy: A bi-national registry-based study

BACKGROUND AND OBJECTIVE

Radical prostatectomy (RP) is a common and widely used treatment for localized prostate cancer. Sequela following RP may include urinary incontinence and sexual dysfunction, outcomes which are recorded within a bi-national Prostate Cancer Outcomes Registry. The objective was to report population-wide urinary incontinence and sexual function outcomes recorded at 12 months following RP; and to quantify and explore factors associated with variation in outcome.

MATERIALS AND METHODS

The Prostate Cancer Outcomes Registry of Australia and New Zealand (PCOR-ANZ) was used for this study. Participants were treated with radical prostatectomy between 2016 and 2020. Domain summary scores for urinary incontinence and sexual function from the EPIC-26 instrument were the main outcomes, taken at 12 months following surgery (6-18 months). "Major" urinary and sexual function bother were also assessed. Variation in outcomes was investigated using linear and logistic multivariable regression models adjusted for covariates: age, socioeconomic status, PSA at diagnosis, surgical technique, surgical specimen grade group, margin status, and clinician surgical volume.

RESULTS AND CONCLUSIONS

The analytic cohort included 13,083 men with the mean urinary incontinence domain score being 76/100 (SD = 25) with 9.2% reporting major bother. For sexual function, the mean score was 29/100 (SD = 26) with 46% reporting major bother. Of the examined variables, age at surgery and surgical volume category were most predictive of function, with disparities exceeding minimally important differences, though large variation was observed between urologists within volume categories. There is considerable variation in 12-month postprostatectomy functional outcomes. Variation is explained by both patient and clinician factors, though some confounders are unmeasured in this cohort.

Development of a Prediction Model for Positive Surgical Margin in Robot-Assisted Laparoscopic Radical Prostatectomy

A positive surgical margin (PSM) is reported to have some connection to the occurrence of biochemical recurrence and tumor metastasis in prostate cancer after the operation. There are no clinically usable models and the study is to predict the probability of PSM after robot-assisted laparoscopic radical prostatectomy (RALP) based on preoperative examinations. It is a retrospective cohort from a single center. The Lasso method was applied for variable screening; logistic regression was employed to establish the final model; the strengthened bootstrap method was adopted for model internal verification; the nomogram and web calculator were used to visualize the model. All the statistical analyses were based on the R-4.1.2. The main outcome was a pathologically confirmed PSM. There were 151 PSMs in the 903 patients, for an overall positive rate of 151/903 = 16.7%; 0.727 was the adjusted C statistic, and the Brier value was 0.126. Hence, we have developed and validated a predictive model for PSM after RALP for prostate cancer that can be used in clinical practice. In the meantime, we observed that the International Society of Urological Pathology (ISUP) score, Prostate Imaging Reporting and Data System (PI-RADS) score, and Prostate-Specific Antigen (PSA) were the independent risk factors for PSM.

Blood Prostate-specific Antigen by Volume of Benign, Gleason Pattern 3 and 4 Prostate Tissue

OBJECTIVE

To evaluate how blood levels of prostate-specific antigen (PSA) relate to prostate volume of benign tissue, Gleason pattern 3 (GP3) and Gleason pattern 4 (GP4) cancer.

METHODS

The cohort included 2209 consecutive men undergoing radical prostatectomy at 2 academic institutions with pT2N0, Grade Group 1-4 prostate cancer and an undetectable postoperative PSA. Volume of benign, GP3, and GP4 were estimated. The primary analysis evaluated the association between PSA and volume of each type of tissue using multivariable linear regression. R2, a measure of explained variation, was calculated using a multivariable model.

RESULTS

Estimated contribution to PSA was 0.04/0.06 ng/mL/cc for benign, 0.08/0.14 ng/mL/cc for GP3, and 0.62/0.80 ng/ml/cc for GP4 for the 2 independent cohorts, respectively. GP4 was associated with 6 to 8-fold more PSA per cc compared to GP3 and 15-fold higher compared to benign tissue. We did not observe a difference between PSA per cc for GP3 vs. benign tissue (P = 0.2). R2 decreased only slightly when removing age (0.006/0.018), volume of benign tissue (0.051/0.054) or GP3 (0.014/0.023) from the model. When GP4 was removed, R2 decreased 0.051/0.310. PSA density (PSA divided by prostate volume) was associated with volume of GP4 but not GP3, after adjustment for benign volume.

CONCLUSION

Gleason pattern 4 cancer contributes considerably more to PSA and PSA density per unit volume compared to GP3 and benign tissue. Contributions from GP3 and benign are similar. Further research should examine the utility of determining clinical management recommendations by absolute volume of GP4 rather than the ratio of GP3 to GP4.

Clonal relationships of adjacent Gleason pattern 3 and Gleason pattern 5 lesions in Gleason Scores 3+5=8 and 5+3=8

Genomic studies have demonstrated a high level of intra-tumoral heterogeneity in prostate cancer. There is strong evidence suggesting that individual tumor foci can arise as genetically distinct, clonally independent lesions. However, recent studies have also demonstrated that adjacent Gleason pattern (GP) 3 and GP4 lesions can originate from the same clone but follow divergent genetic and morphologic evolution. The clonal relationship of adjacent GP3 and GP5 lesions has thus far not been investigated. Here we analyzed a cohort of 14 cases-11 biopsy and 3 radical prostatectomy specimens-with a Gleason score of 3 + 5 = 8 or 5 + 3 = 8 present in the same biopsy or in a single dominant tumor nodule at radical prostatectomy. Clonal and subclonal relationships between GP3 and GP5 lesions were assessed using genetically validated immunohistochemical assays for ERG, PTEN, and P53. 9/14 (64%) cases showed ERG reactivity in both GP3 and GP5 lesions. Only 1/14 (7%) cases showed a discordant pattern with ERG staining present only in GP3. PTEN expression was lost in 2/14 (14%) cases with perfect concordance between GP5 and GP3. P53 nuclear reactivity was present in 1/14 (7%) case in both GP5 and GP3. This study provides first evidence that the majority of adjacent GP3 and GP5 lesions share driver alterations and are clonally related. In addition, we observed a lower-than-expected rate of PTEN loss in GP5 in the context of Gleason score 3 + 5 = 8 or 5 + 3 = 8 tumors.

Modified the 8th AJCC staging system for patients with advanced prostate cancer: a study based on SEER database

Background

The American Joint Committee on Cancer (AJCC) 8th staging system of prostate cancer may be insufficient in predicting the prognosis of some staged patients. This study aimed to modify the AJCC 8th staging system in patients with advanced prostate cancer.

Methods

Data of patients with advanced prostate cancer from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2016 were enrolled in this cohort study. All patients were divided into the training set and the testing set with a ratio of 6:4. Multivariate Cox survival model was utilized to obtain the nomogram score for each stage variable. The modified staging system was based on the total nomogram score. The C-index and Kaplan-Meier (K-M) curves were used to show the prognostic prediction effect of patients with different staging systems.

Results

A total of 28,006 patients were included for analysis. T stage, N stage, M stage, primary Gleason pattern score, secondary Gleason pattern score, and PSA level were included as stage variables. Patients with AJCC stage III C [hazard ratio (HR) = 4.17, 95% confidence interval (CI), 3.39–5.13] and AJCC stage IV B (HR = 3.19, 95%CI, 1.79–5.69) were associated with worse prognosis compared with those of AJCC stage III B, while no statistical significance was found in patients with stage IV A (P > 0.05). In terms of the modified staging system, patients with modified stage III C (HR = 2.06, 95%CI, 1.46–2.92), modified stage IV A (HR = 6.91, 95%CI, 4.81–9.94), and modified stage IV B (HR = 21.89, 95%CI, 14.76–32.46) were associated with a poorer prognosis compared with patients with modified stage III B. The prognostic ability (C-index) of the modified staging system (0.789; 95%CI, 0.777–0.801) was better than that of the AJCC 8th edition system (0.762; 95%CI, 0.748–0.776) (0.789 vs. 0.762, P = 0.004). The K-M curves indicated that the modified staging system may be distinguished prognostic differences in patients with different stages.

Conclusion

Modified staging system may be better than AJCC 8th staging system for predicting prognosis in prostate cancer patients. The AJCC 8th staging system should be further optimized.

Single cell analysis of cribriform prostate cancer reveals cell intrinsic and tumor microenvironmental pathways of aggressive disease

Cribriform prostate cancer, found in both invasive cribriform carcinoma (ICC) and intraductal carcinoma (IDC), is an aggressive histological subtype that is associated with progression to lethal disease. To delineate the molecular and cellular underpinnings of ICC/IDC aggressiveness, this study examines paired ICC/IDC and benign prostate surgical samples by single-cell RNA-sequencing, TCR sequencing, and histology. ICC/IDC cancer cells express genes associated with metastasis and targets with potential for therapeutic intervention. Pathway analyses and ligand/receptor status model cellular interactions among ICC/IDC and the tumor microenvironment (TME) including JAG1/NOTCH. The ICC/IDC TME is hallmarked by increased angiogenesis and immunosuppressive fibroblasts (CTHRC1⁺ASPN⁺FAP⁺ENG⁺) along with fewer T cells, elevated T cell dysfunction, and increased C1QB⁺TREM2⁺APOE⁺-M2 macrophages. These findings support that cancer cell intrinsic pathways and a complex immunosuppressive TME contribute to the aggressive phenotype of ICC/IDC. These data highlight potential therapeutic opportunities to restore immune signaling in patients with ICC/IDC that may afford better outcomes.

Increased Density of Growth Differentiation Factor-15+ Immunoreactive M1/M2 Macrophages in Prostate Cancer of Different Gleason Scores Compared with Benign Prostate Hyperplasia

Simple Summary

Prostate cancer (PCa) is the second most diagnosed cancer and cause of death in men worldwide. The main challenge is to discover biomarkers for malignancy to guide the physician towards optimized diagnosis and therapy. There is recent evidence that growth differentiation factor-15 (GDF-15) is elevated in cancer patients. Therefore, we aimed to decipher GDF-15+ cell types and their density in biopsies of human PCa patients with Gleason score (GS)6–9 and benign prostate hyperplasia (BPH). Here we show that the density of GDF-15+ cells, mainly identified as interstitial macrophages (MΦ), was higher in GS6–9 than in BPH, and, thus, GDF-15 is intended to differentiate patients with high GS vs. BPH, as well as GS6 vs. GS7 (or even with higher malignancy). Some GDF-15+ MΦ showed a transepithelial migration into the glandular lumen and, thus, might be used for measurement in urine/semen. Taken together, GDF-15 is proposed as a novel tool to diagnose PCa vs. BPH or malignancy (GS6 vs. higher GS) and as a potential target for anti-tumor therapy. GDF-15 in seminal plasma and/or urine could be utilized as a non-invasive biomarker of PCa as compared to BPH.

Abstract

Although growth differentiation factor-15 (GDF-15) is highly expressed in PCa, its role in the development and progression of PCa is unclear. The present study aims to determine the density of GDF-15+ cells and immune cells (M1-/M2 macrophages [MΦ], lymphocytes) in PCa of different Gleason scores (GS) compared to BPH. Immunohistochemistry and double immunofluorescence were performed on paraffin-embedded human PCa and BPH biopsies with antibodies directed against GDF-15, CD68 (M1 MΦ), CD163 (M2 MΦ), CD4, CD8, CD19 (T /B lymphocytes), or PD-L1. PGP9.5 served as a marker for innervation and neuroendocrine cells. GDF-15+ cell density was higher in all GS than in BPH. CD68+ MΦ density in GS9 and CD163+ MΦ exceeded that in BPH. GDF-15+ cell density correlated significantly positively with CD68+ or CD163+ MΦ density in extratumoral areas. Double immunoreactive GDF-15+/CD68+ cells were found as transepithelial migrating MΦ. Stromal CD68+ MΦ lacked GDF-15+. The area of PGP9.5+ innervation was higher in GS9 than in BPH. PGP9.5+ cells, occasionally copositive for GDF-15+, also occurred in the glandular epithelium. In GS6, but not in BPH, GDF-15+, PD-L1+, and CD68+ cells were found in epithelium within luminal excrescences. The degree of extra-/intra-tumoral GDF-15 increases in M1/M2Φ is proposed to be useful to stratify progredient malignancy of PCa. GDF-15 is a potential target for anti-tumor therapy.

Prediction of Adverse Pathology at Radical Prostatectomy in Grade Group 2 and 3 Prostate Biopsies Using Machine Learning

PURPOSE

There is ongoing clinical need to improve estimates of disease outcome in prostate cancer. Machine learning (ML) approaches to pathologic diagnosis and prognosis are a promising and increasingly used strategy. In this study, we use an ML algorithm for prediction of adverse outcomes at radical prostatectomy (RP) using whole-slide images (WSIs) of prostate biopsies with Grade Group (GG) 2 or 3 disease.

METHODS

We performed a retrospective review of prostate biopsies collected at our institution which had corresponding RP, GG 2 or 3 disease one or more cores, and no biopsies with higher than GG 3 disease. A hematoxylin and eosin-stained core needle biopsy from each site with GG 2 or 3 disease was scanned and used as the sole input for the algorithm. The ML pipeline had three phases: image preprocessing, feature extraction, and adverse outcome prediction. First, patches were extracted from each biopsy scan. Subsequently, the pre-trained Visual Geometry Group-16 convolutional neural network was used for feature extraction. A representative feature vector was then used as input to an Extreme Gradient Boosting classifier for predicting the binary adverse outcome. We subsequently assessed patient clinical risk using CAPRA score for comparison with the ML pipeline results.

RESULTS

The data set included 361 WSIs from 107 patients (56 with adverse pathology at RP). The area under the receiver operating characteristic curves for the ML classification were 0.72 (95% CI, 0.62 to 0.81), 0.65 (95% CI, 0.53 to 0.79) and 0.89 (95% CI, 0.79 to 1.00) for the entire cohort, and GG 2 and GG 3 patients, respectively, similar to the performance of the CAPRA clinical risk assessment.

CONCLUSION

We provide evidence for the potential of ML algorithms to use WSIs of needle core prostate biopsies to estimate clinically relevant prostate cancer outcomes.

Clinical utility of histopathology data: urological cancers

Cancer datasets recommend standardised reporting of histopathological data items with elements categorised as either core (required) or non-core (recommended), irrespective of the clinical scenario. However, the clinical significance of a data item in an individual case would depend on the clinicopathological setting as well as local management guidelines. A data item that is critical for patient management in one clinical scenario may be largely irrelevant in another patient. Pathologists must understand how their data are used in clinical practice so that they can focus their limited resources appropriately. We briefly review the use of histopathological data in the management of urological cancers, highlighting scenarios where a data item may be of limited clinical utility.

Comparison between biparametric and multiparametric MRI diagnosis strategy for prostate cancer in the peripheral zone using PI-RADS version 2.1

PURPOSE

To compare and analyse the diagnostic value of PI-RADS v2.1 when used with biparametric MRI (bpMRI) versus multiparametric MRI (mpMRI), DWI versus T2WI to detect peripheral-zone prostate cancer (pzPCa) and clinically significant peripheral-zone prostate cancer (cs-pzPCa).

METHODS

The diagnostic efficiencies of mpMRI and bpMRI as well as DWI and T2WI in pzPCa and cs-pzPCa were compared using a PI-RADS score of ≥ 4 as the positive threshold and prostate biopsy and radical prostatectomy as the reference standards.

RESULTS

A total of 307 prostate cases were included in the study, including 142 in the non-pzPCa group, 165 in the pzPCa group, and 130 in the cs-pzPCa group. The AUCs of mpMRI and bpMRI were 0.717 and 0.733 (P = 0.317), respectively, for the diagnosis of pzPCa (sensitivities: 89.1% and 81.8%; specificities: 54.2% and 64.8%, both P < 0.001) and 0.594 and 0.602 (P = 0.756), respectively, for the diagnosis of cs-pzPCa (sensitivities: 93.1% and 86.2%, P = 0.004; specificities: 25.7% and 34.3%, P = 0.250). The AUCs of DWI and T2WI were 0.733 and 0.749 (P = 0.308), respectively, for the diagnosis of pzPCa (sensitivities: 81.8% and 84.2%; specificities: 64.8% and 66.2%, both P > 0.05) and 0.602 and 0.581 (P = 0.371), respectively, for the diagnosis of cs-pzPCa (sensitivities: 86.2% and 87.7%; specificities: 34.3% and 28.6%, both P > 0.05).

CONCLUSION

mpMRI and bpMRI as well as DWI and T2WI using PI-RADS v2.1 exhibited similar diagnostic efficiency in pzPCa and cs-pzPCa.

Rapid Histological Assessment of Prostate Specimens in the Three-dimensional Space by Hydrophilic Tissue Clearing and Confocal Microscopy

Microscopic examination of biopsied and resected prostatic specimens is the mainstay in the diagnosis of prostate cancer. However, conventional analysis of hematoxylin and eosin (H&E)-stained tissue is time-consuming and offers limited two-dimensional (2D) information. In the current study, we devised a method-termed Prostate Rapid Optical examination for cancer STATus (proSTAT)-for rapid screening of prostate cancer using high-resolution 2D and three-dimensional (3D) confocal images obtained after hydrophilic tissue clearing of 100-µm-thick tissue slices. The results of the proSTAT method were compared with those of traditional H&E stains for the analysis of cores (n=15) obtained from radical prostatectomy specimens (n=5). Gland lumen formation, consistent with Gleason pattern 3, was evident following tracking of multiple optical imaging sections. In addition, 3D rendering allowed visualizing a tubular network of interconnecting branches. Rapid 3D fluorescent labeling of tumor protein p63 accurately distinguished prostate adenocarcinoma from normal tissue and benign lesions. Compared with conventional stains, the 3D spatial and molecular information extracted from proSTAT may significantly increase the amount of available data for pathological assessment of prostate specimens. Our approach is amenable to automation and-subject to independent validation-can find a wide spectrum of clinical and research applications.

Magnetic Resonance Imaging-Targeted Biopsy and Pretherapeutic Prostate Cancer Risk Assessment: a Systematic Review: Biopsie ciblée par Imagerie par résonance magnétique et évaluation pré-thérapeutique du risque de cancer de la prostate : revue systématique

INTRODUCTION

Multiparametric magnetic resonance imaging (MRI) has been included in prostate cancer (PCa) diagnostic pathway and may improve disease characterization. The aim of this systematic review is to assess the added value of MRI-targeted biopsy (TB) in pre-therapeutic risk assessment models over existing tools based on systematic biopsy (SB) for localized PCa.

EVIDENCE ACQUISITION

A systematic search was conducted using Pubmed (Medline), Scopus and ScienceDirect databases according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. We included studies through October 2021 reporting on TB in pretherapeutic risk assessment models.

EVIDENCE SYNTHESIS

We identified 24 eligible studies including 24'237 patients for the systematic review. All included studies were retrospective and conducted in patients undergoing radical prostatectomy. Nine studies reported on the risk of extraprostatic extension, seven on the risk of lymph node invasion, three on the risk of biochemical recurrence and nine on the improvement of PCa risk stratification. Overall, the combination of TB with imaging, clinical and biochemical parameters outperformed current pretherapeutic risk assessment models. External validation studies are lacking for certain endpoints and the absence of standardization among TB protocols, including number of TB cores and fusion systems, may limit the generalizability of the results.

CONCLUSION

TB should be incorporated in pretherapeutic risk assessment models to improve clinical decision making. Further high-quality studies are required to determine models' generalizability while there is an urgent need to reach consensus on a standardized TB protocol. Long-term outcomes after treatment are also awaited to confirm the superiority of such models over classical risk classifications only based on SB. © 2022 Elsevier Masson SAS. All rights reserved.