Prognostic value of the Gleason score in prostate cancer

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

Towards Digital Quantification of Ploidy from Pan-Cancer Digital Pathology Slides using Deep Learning

Abnormal DNA ploidy, found in numerous cancers, is increasingly being recognized as a contributor in driving chromosomal instability, genome evolution, and the heterogeneity that fuels cancer cell progression. Furthermore, it has been linked with poor prognosis of cancer patients. While next-generation sequencing can be used to approximate tumor ploidy, it has a high error rate for near-euploid states, a high cost and is time consuming, motivating alternative rapid quantification methods. We introduce PloiViT, a transformer-based model for tumor ploidy quantification that outperforms traditional machine learning models, enabling rapid and cost-effective quantification directly from pathology slides. We trained PloiViT on a dataset of fifteen cancer types from The Cancer Genome Atlas and validated its performance in multiple independent cohorts. Additionally, we explored the impact of self-supervised feature extraction on performance. PloiViT, using self-supervised features, achieved the lowest prediction error in multiple independent cohorts, exhibiting better generalization capabilities. Our findings demonstrate that PloiViT predicts higher ploidy values in aggressive cancer groups and patients with specific mutations, validating PloiViT potential as complementary for ploidy assessment to next-generation sequencing data. To further promote its use, we release our models as a user-friendly inference application and a Python package for easy adoption and use.

External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens

OBJECTIVES

To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole-mount prostate histopathology, considering potential variations observed when applying AI models trained on biopsy samples to radical prostatectomy (RP) specimens due to inherent differences in tissue representation and sample size.

MATERIALS AND METHODS

The commercially available DeepDx Prostate AI algorithm is an automated Gleason grading system that was previously trained using 1133 prostate core biopsy images and validated on 700 biopsy images from two institutions. We assessed the AI algorithm's performance, which outputs Gleason patterns (3, 4, or 5), on 500 1-mm2 tiles created from 150 whole-mount RP specimens from a third institution. These patterns were then grouped into grade groups (GGs) for comparison with expert pathologist assessments. The reference standard was the International Society of Urological Pathology GG as established by two experienced uropathologists with a third expert to adjudicate discordant cases. We defined the main metric as the agreement with the reference standard, using Cohen's kappa.

RESULTS

The agreement between the two experienced pathologists in determining GGs at the tile level had a quadratically weighted Cohen's kappa of 0.94. The agreement between the AI algorithm and the reference standard in differentiating cancerous vs non-cancerous tissue had an unweighted Cohen's kappa of 0.91. Additionally, the AI algorithm's agreement with the reference standard in classifying tiles into GGs had a quadratically weighted Cohen's kappa of 0.89. In distinguishing cancerous vs non-cancerous tissue, the AI algorithm achieved a sensitivity of 0.997 and specificity of 0.88; in classifying GG ≥2 vs GG 1 and non-cancerous tissue, it demonstrated a sensitivity of 0.98 and specificity of 0.85.

CONCLUSION

The DeepDx Prostate AI algorithm had excellent agreement with expert uropathologists and performance in cancer identification and grading on RP specimens, despite being trained on biopsy specimens from an entirely different patient population.

Ribosome-binding protein-1 (RRBP1) expression in prostate carcinomas and its relationship with clinicopathological prognostic factors

INTRODUCTION

Studies in recent years have shown that ribosome-binding protein-1 (RRBP1) is expressed at high rates in many cancers and that it may be a potential prognostic biomarker. The objective of the present study is to determine the RRBP1 expression level in prostatic carcinoma and neighboring non-neoplastic prostate tissue, the relationship between its expression level with prognostic factors, and the role of RRBP1 in the development of prostate cancer.

MATERIALS AND METHODS

The study included 45 patients who were diagnosed with prostatic carcinoma and underwent radical prostatectomy in our center between the years 2010 and 2021. Pathology reports were reviewed. Mann-Whitney U test was used for the comparison of RRBP1 and GADPH values of the cases (control and tumoral tissue) between the primary tumor stage (pT) and Gleason score (GS) groups. Hierarchical regression analysis was used to explain the effective variables in explaining the RRBP1 value of the research cases.

RESULTS

According to the Mann-Whitney U test, mean and median RRBP1-T values of the cases with GS ≥ 8 were detected to be statistically significantly higher than the mean and median RRBP1-T values of the cases with GS < 8.

CONCLUSION

We found out that RRBP1 was expressed at higher rates in patients with high GS and advanced-stage patients. This result indicated that RRBP1 expression may be important in predicting the prognosis of prostate carcinoma.

Prostate cancer research: tools, cell types, and molecular targets

Multiple cancer cell types are found in prostate tumors. They are either luminal-like adenocarcinoma or less luminal-like and more stem-like non-adenocarcinoma and small cell carcinoma. These types are lineage related through differentiation. Loss of cancer differentiation from luminal-like to stem-like is mediated by the activation of stem cell transcription factors (scTF) such as LIN28A, NANOG, POU5F1 and SOX2. scTF expression leads to down-regulation of β2-microglobulin (B2M). Thus, cancer cells can change from the scT F ˜ B 2 M hi phenotype of differentiated to that of scT F ˙ B 2 M lo of dedifferentiated in the disease course. In development, epithelial cell differentiation is induced by stromal signaling and cell contact. One of the stromal factors specific to prostate encodes proenkephalin (PENK). PENK can down-regulate scTF and up-regulate B2M in stem-like small cell carcinoma LuCaP 145.1 cells indicative of exit from the stem state and differentiation. In fact, prostate cancer cells can be made to undergo dedifferentiation or reprogramming by scTF transfection and then to differentiate by PENK transfection. Therapies need to be designed for treating the different cancer cell types. Extracellular anterior gradient 2 (eAGR2) is an adenocarcinoma antigen associated with cancer differentiation that can be targeted by antibodies to lyse tumor cells with immune system components. eAGR2 is specific to cancer as normal cells express only the intracellular form (iAGR2). For AGR2-negative stem-like cancer cells, factors like PENK that can target scTF could be effective in differentiation therapy.

Descriptive analysis of prostate cancer pathology data from diagnosis and surgery in men from the 45 and Up Study

Information available from the New South Wales Cancer Registry (NSWCR) about the aggressiveness of prostate cancer is limited to the summary stage variable 'degree of spread', which contains a high proportion of cases defined as 'unknown'. In this study we demonstrate the feasibility of obtaining and analysing prostate cancer pathology data from stored pathology records. Pathology data were extracted from stored pathology records of incident prostate cancer cases in men participating in the 45 and Up Study, a large Australian prospective cohort study, who were diagnosed between January 2006 and December 2013. Baseline questionnaires from the 45 and Up Study were linked to the NSWCR. Demographic and pathology items were tabulated and associations described. We evaluated the completeness of pathological characteristics by degree of spread of cancer at diagnosis. Among the 123,921 men enrolled in the 45 and Up Study, 5,091 had incident prostate cancer and 5,085 were linked to a pathology record. The most complete variables included grade group of diagnostic (85.8%) and surgical (99.8%) specimens, margin status (98.1%), extraprostatic extension (95.1%) and seminal vesicle invasion (96.8%). Most diagnostic specimens were grade group 1 (26.6%) or 2 (23.5%). Of the 5,085 cases, 30.8% were classified by the NSWCR with unknown degree of spread; a pathology record could be extracted for 99.4% of these. The unknown degree of spread cases had similar levels of completeness and distribution of diagnostic and surgical pathology features to those with a localised degree of spread. This study demonstrated the feasibility of obtaining and analysing data derived from pathology reports from centralised state-based cancer registry notifications. Supplementing degree of spread information with pathology data from diagnosis and surgery will improve both the quality of research and policy aimed at improving the lives of men with prostate cancer.

Graph-based multi-modality integration for prediction of cancer subtype and severity

Personalised cancer screening before therapy paves the way toward improving diagnostic accuracy and treatment outcomes. Most approaches are limited to a single data type and do not consider interactions between features, leaving aside the complementary insights that multimodality and systems biology can provide. In this project, we demonstrate the use of graph theory for data integration via individual networks where nodes and edges are individual-specific. We showcase the consequences of early, intermediate, and late graph-based fusion of RNA-Seq data and histopathology whole-slide images for predicting cancer subtypes and severity. The methodology developed is as follows: (1) we create individual networks; (2) we compute the similarity between individuals from these graphs; (3) we train our model on the similarity matrices; (4) we evaluate the performance using the macro F1 score. Pros and cons of elements of the pipeline are evaluated on publicly available real-life datasets. We find that graph-based methods can increase performance over methods that do not study interactions. Additionally, merging multiple data sources often improves classification compared to models based on single data, especially through intermediate fusion. The proposed workflow can easily be adapted to other disease contexts to accelerate and enhance personalized healthcare.

Outlook of Gleason score in prostate carcinoma and correlation with PSA levels: A study in a tertiary care hospital

Introduction

In India, prostate carcinoma is the fifth most common cause of carcinoma in men, and the fourth in cancer mortality. Incidence of prostate malignancy is increasing in India by one percent every year. Prostate carcinoma is graded using the Gleason scoring system. The Gleason score is very useful for predicting the prognosis of prostate carcinoma. The collaborative use of clinical features, combined with the size of the prostate, prostate-specific antigen levels, and histopathological features helps in making an accurate and early diagnosis of the patients.

Material and Method

This present prospective study included all histologically proven cases of prostate carcinoma in the Department of Pathology, Guru Gobind Singh Medical Hospital over a period of one year. A detailed histopathological examination of the H and E stained sections is carried out under light microscope including histological typing, Gleason scoring and grading. The Gleason grade was correlated with serum PSA levels.

Results

Out of 80 cases, 28 (35%) were reported as Gleason grade group 3 with a Gleason score of 7 (4 + 3). 12 cases (15%) showed a Gleason grade group 2 with a Gleason score of 7 (3 + 4). Grade group 4 (Gleason score 8) and grade group 5 were observed in 22 cases (27.5%) and 18 cases (22.5%), respectively. Whereas, no case of Gleason grade group 1 with Gleason score of 6 (3 + 3) was seen.

Conclusion

Gleason's Group Grade 3 outnumbered all the group grades, contributing 35% (28 cases) of the total cases of prostatic adenocarcinoma. Serum PSA levels were raised (>10 ng/ml) in 100% of cases. Henceforth, it signifies the importance of serum PSA levels in prostate carcinoma. Lymphovascular invasion was associated with higher group grade of prostatic adenocarcinoma.

PSMA-heterogeneity in metastatic castration-resistant prostate cancer: Circulating tumor cells, metastatic tumor burden, and response to targeted radioligand therapy

BACKGROUND

We explored the interrelation between prostate-specific membrane antigen (PSMA) expression on circulating tumor cells (CTCs) and that of solid metastatic lesions as determined by whole-body PSMA-targeted positron emission tomography (PET) to refine the prediction of response to subsequent PSMA-targeted radioligand therapy (RLT).

METHODS

A prospective study was performed in 20 patients with advanced mCRPC. Of these, 16 underwent subsequent RLT with [¹⁷⁷ Lu]Lu-PSMA-617 at a dose of 7.4 GBq every 6-8 weeks. PSMA expression on CTCs using the CellSearch system was compared to clinical and serological results, and to marker expression in targeted imaging and available histological sections of prostatectomy specimens (19% of RLT patients). Clinical outcome was obtained after two cycles of RLT.

RESULTS

Marked heterogeneity of PSMA expression was observed already at first diagnosis in available histological specimens. Targeted whole-body imaging also showed heterogeneous inter- and intra-patient PSMA expression between metastases. Heterogeneity of CTC PSMA expression was partially paralleled by heterogeneity of whole-body tumor burden PSMA expression. Twenty percent of CTC samples showed no PSMA expression, despite unequivocal PSMA expression of solid metastases at PET. A high fraction of PSMA-negative CTCs emerged as the sole predictor of poor RLT response (odds ratio [OR]: 0.9379 [95% confidence interval, CI, 0.8558-0.9902]; p = 0.0160), and was prognostic for both shorter progression-free survival (OR: 1.236 [95% CI, 1.035-2.587]; p = 0.0043) and overall survival (OR: 1.056 [95% CI, 1.008-1.141]; p = 0.0182).

CONCLUSION

This proof-of-principle study suggests that liquid biopsy for CTC PSMA expression is complementary to PET for individual PSMA phenotyping of mCRPC.

Ki67 and the apparent diffusion coefficient in postoperative prostate cancer with endocrine therapy

Background

Prostate-specific antigen (PSA) is a critical part of prostate cancer (PCa) screening, diagnosis, staging, and prognosis. However, elevated PSA levels can also be caused by several external factors. To improve the specificity and sensitivity of PSA in clinical practice, we explored whether markers or parameters may be used as prognostic targets for PCa by long-term follow-up.

Methods

A total of 121 PCa patients who underwent laparoscopic radical prostatectomy (LRP) were included in our study, all of whom underwent imaging and preoperative pathological diagnosis. Endocrine therapy has long been applied to treat postoperative patients. The prognosis of enrolled patients was followed, and statistics were collected. Spearman's correlation analysis was applied to examine the relationship and clinical parameters. Kaplan–Meier analysis was used to process the clinical variables of PCa patients. Cox proportional hazards regression analysis was applied to examine univariate and multivariate variables.

Results

The Gleason score (GS), PSA, clinical stage, nerve infiltration, organ confinement, Ki67 and apparent diffusion coefficient (ADC) were significantly associated with prognosis (all P &lt; 0.05). The GS, PSA, clinical stage, organ confined, Ki67, nerve infiltration and ADC were included in the multivariate analysis (all P &lt; 0.05). Ultimately, Ki67 and the ADC were found to provide meaningful predictive information (both P &lt; 0.05).

Conclusions

Ki67 and the ADC may be clinically and analytically valid prognostic biomarkers and imaging parameters in PCa. They may be useful for predicting the prognosis and risk of PCa patients undergoing postoperative routine endocrine therapy.

A Highly Sensitive Urinary Exosomal miRNAs Biosensor Applied to Evaluation of Prostate Cancer Progression

Prostate cancer is the most common cancer in the male population, carrying a significant disease burden. PSA is a widely available screening tools for this disease. Current screen-printed carbon electrode (SPCE)-based biosensors use a two-pronged probe approach to capture urinary miRNA. We were able to successfully detect specific exosomal miRNAs (exomiRs) in the urine of patients with prostate cancer, including exomiR-451 and exomiR-21, and used electrochemistry for measurement and analysis. Our results significantly reaffirmed the presence of exomiR-451 in urine and that a CV value higher than 220 nA is capable of identifying the presence of disease (p-value = 0.005). Similar results were further proven by a PAS greater than 4 (p-value = 0.001). Moreover, a higher urinary exomiR-21 was observed in the high-T3b stage; this significantly decreased following tumor removal (p-values were 0.016 and 0.907, respectively). According to analysis of the correlation with tumor metastasis, a higher exomiR-21 was associated with lymphatic metastasis (p-value 0.042), and higher exomiR-461 expression was correlated with tumor stage (p-value 0.031), demonstrating that the present exomiR biosensor can usefully predict tumor progression. In conclusion, this biosensor represents an easy-to-use, non-invasive screening tool that is both sensitive and specific. We strongly believe that this can be used in conjunction with PSA for the screening of prostate cancer.

Comparative Performance of Deep Learning and Radiologists for the Diagnosis and Localization of Clinically Significant Prostate Cancer at MRI: A Systematic Review

Background: Deep learning (DL)-based models have demonstrated an ability to automatically diagnose clinically significant prostate cancer (PCa) on MRI scans and are regularly reported to approach expert performance. The aim of this work was to systematically review the literature comparing deep learning (DL) systems to radiologists in order to evaluate the comparative performance of current state-of-the-art deep learning models and radiologists. Methods: This systematic review was conducted in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Studies investigating DL models for diagnosing clinically significant (cs) PCa on MRI were included. The quality and risk of bias of each study were assessed using the checklist for AI in medical imaging (CLAIM) and QUADAS-2, respectively. Patient level and lesion-based diagnostic performance were separately evaluated by comparing the sensitivity achieved by DL and radiologists at an identical specificity and the false positives per patient, respectively. Results: The final selection consisted of eight studies with a combined 7337 patients. The median study quality with CLAIM was 74.1% (IQR: 70.6–77.6). DL achieved an identical patient-level performance to the radiologists for PI-RADS ≥ 3 (both 97.7%, SD = 2.1%). DL had a lower sensitivity for PI-RADS ≥ 4 (84.2% vs. 88.8%, p = 0.43). The sensitivity of DL for lesion localization was also between 2% and 12.5% lower than that of the radiologists. Conclusions: DL models for the diagnosis of csPCa on MRI appear to approach the performance of experts but currently have a lower sensitivity compared to experienced radiologists. There is a need for studies with larger datasets and for validation on external data.

Association of adenosine signaling gene signature with estrogen receptor-positive breast and prostate cancer bone metastasis

Bone metastasis is a common and devastating consequence of several major cancer types, including breast and prostate. Osteocytes are the predominant bone cell, and through connexin (Cx) 43 hemichannels release ATP to the bone microenvironment that can be hydrolyzed to adenosine. Here, we investigated how genes related to ATP paracrine signaling are involved in two common bone-metastasizing malignancies, estrogen receptor positive (ER⁺) breast and prostate cancers. Compared to other sites, bone metastases of both cancer types expressed higher levels of ENTPD1 and NT5E, which encode CD39 and CD73, respectively, and hydrolyze ATP to adenosine. ADORA3, encoding the adenosine A3 receptor, had a similar expression pattern. In primary ER⁺ breast cancer, high levels of the triplet ENTPD1/NT5E/ADORA3 expression signature was correlated with lower overall, distant metastasis-free, and progression-free survival. In ER⁺ bone metastasis biopsies, this expression signature is associated with lower survival. This expression signature was also higher in bone-metastasizing primary prostate cancers than in those that caused other tumor events or did not lead to progressive disease. In 3D culture, a non-hydrolyzable ATP analog inhibited the growth of breast and prostate cancer cell lines more than ATP did. A3 inhibition also reduced spheroid growth. Large-scale screens by the Drug Repurposing Hub found ER⁺ breast cancer cell lines were uniquely sensitive to adenosine receptor antagonists. Together, these data suggest a vital role for extracellular ATP degradation and adenosine receptor signaling in cancer bone metastasis, and this study provides potential diagnostic means for bone metastasis and specific targets for treatment and prevention.

Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa

BACKGROUND

Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa.

RESULTS

Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608-0.707, OR 2.37-5.71) than for African individuals (AUC 0.502-0.585, OR 0.95-2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores.

CONCLUSIONS

Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.

Prediction of disease progression indicators in prostate cancer patients receiving HDR-brachytherapy using Raman spectroscopy and semi-supervised learning: a pilot study

This work combines Raman spectroscopy (RS) with supervised learning methods-group and basis restricted non-negative matrix factorisation (GBR-NMF) and linear discriminant analysis (LDA)-to aid in the prediction of clinical indicators of disease progression in a cohort of 9 patients receiving high dose rate brachytherapy (HDR-BT) as the primary treatment for intermediate risk (D'Amico) prostate adenocarcinoma. The combination of Raman spectroscopy and GBR-NMF-sparseLDA modelling allowed for the prediction of the following clinical information; Gleason score, cancer of the prostate risk assessment (CAPRA) score of pre-treatment biopsies and a Ki67 score of < 3.5% or > 3.5% in post treatment biopsies. The three clinical indicators of disease progression investigated in this study were predicted using a single set of Raman spectral data acquired from each individual biopsy, obtained pre HDR-BT treatment. This work highlights the potential of RS, combined with supervised learning, as a tool for the prediction of multiple types of clinically relevant information to be acquired simultaneously using pre-treatment biopsies, therefore opening up the potential for avoiding the need for multiple immunohistochemistry (IHC) staining procedures (H&E, Ki67) and blood sample analysis (PSA) to aid in CAPRA scoring.

Fresh tissue procurement and preparation for multicompartment and multimodal analysis of the prostate tumor microenvironment

BACKGROUND

Prostatic cancers include a diverse microenvironment of tumor cells, cancer-associated fibroblasts, and immune components. This tumor microenvironment (TME) is a known driving force of tumor survival after treatment, but the standard-of-care tissue freezing or fixation in pathology practice limit the use of available approaches/tools to study the TME's functionality in tumor resistance. Thus, there is a need for approaches that satisfy both clinical and laboratory endpoints for TME study. Here we present methods for clinical case identification, tissue processing, and analytical workflow that are compatible with standard histopathology while enabling molecular and functional interrogation of prostate TME components.

METHODS

We first performed a small retrospective review to identify cases where submission of alternate prostate tissue slices and a parallel live tissue processing protocol complement traditional histopathology and enable viable multicompartment analysis of the TME. Then, we tested its compatibility with commonly employed methods to study the microenvironment including quantification of components both in situ and after tissue dissociation. We also evaluated tissue digestion conditions and cell isolation techniques to aid various molecular and functional endpoints.

RESULTS

We identified Gleason Grade Group 3+ clinical cases where tumor volume was sufficient to allow slicing of unfixed tissue and distribution of alternating tissue slices to standard-of-care histopathology and viable multi-modal TME analyses. No single method was found that preserved cellular sub-types for all downstream readouts; instead, tissues were further divided so techniques could be catered to each endpoint. For instance, we show that incorporating the protease dispase into tissue dissociation improves viability for culture and functional analyses but hinders immune cell analysis by flow cytometry. We also found that flow activated cell sorting provides highly pure cell populations for quantitative reverse-transcription polymerase chain reaction and RNA-seq while isolation using antibody-labeled paramagnetic particles facilitated functional coculture experiments.

CONCLUSIONS

The identification of candidate cases and use of these techniques enable translational research and the development of molecular and functional assays to facilitate prostate TME study without compromising standard-of-care histopathological diagnosis. This allows bridging clinical histopathology and further interrogation of the prostate TME and promises to advance our understanding of tumor biology and unveil new predictive and prognostic markers of prostate cancer progression.

Glycemic control was associated with nonprostate cancer and overall mortalities in diabetic patients with prostate cancer

BACKGROUND

Diabetes mellitus (DM) can worsen the prognosis or survival in prostate cancer (PC) patients. We investigated whether glycemic control impacts mortality in PC patients with existing diabetes.

METHODS

All PC patients with or without preexisting DM were enrolled from 2006 to 2017. Mean hemoglobin A1c (HbA1c) values (<7%, 7%-9%, ≥9%) were used to represent glycemic control. Major outcomes included all-cause, PC-specific, and non-PC mortalities. Statistical analyses were performed using Cox regression models with adjusted mean HbA1c and other related confounders.

RESULTS

A total of 831 PC patients were enrolled (non-DM group, n = 690; DM group with a record of mean HbA1c values, n = 141). Results showed that the DM group with mean HbA1c level ≥ 9% (n = 14) had significantly increased risk for all-cause and non-PC mortality (hazard ratio [HR], 3.09; 95% CIs, 1.15-8.32; p=0.025 and HR, 5.49; 95% CIs, 1.66-18.16; p = 0.005, respectively), but not for PC-specific mortality (HR, 1.03; 95% CIs, 0.13-8.44; p = 0.975), compared with the non-DM group.

CONCLUSION

Our findings indicate that PC patients with DM who had a mean HbA1c level ≥ 9% had higher risks of all-cause and non-PC mortality compared with non-DM subjects. Further large and long-term studies are needed to verify the effect of glycemic control in PC patients with DM.

Occupation and prostate Cancer risk: results from the epidemiological study of prostate cancer (EPICAP)

Background

Although prostate cancer (PCa) is the most frequent male cancer in industrialized countries, little is known about its aetiology. The literature has suggested an influence of the environment, including occupational exposures, but results are inconsistent. In this context, we investigated PCa risk associated to employment among several occupations using data from EPICAP study.

Methods

EPICAP is a French population-based case-control study including 819 PCa incident cases and 879 controls frequency-matched on age. In-person interviews gathered data on potential risk factors and lifetime occupational histories for each job held at least 6 months. Then, occupations were coded using ISCO 68. Unconditional logistic regressions were performed to assess the association between occupations (ever occupied and by duration) and PCa risk, whether all and aggressive, after adjusting for potential confounders.

Results

For ≥10 years of employment, we found positive associations with PCa, whether overall and aggressive, among Medical, Dental and Veterinary workers (OR (odds ratios) =5.01 [95% confidence interval] [1.27; 19.77]), Members of the armed forces (OR = 5.14 [0.99; 26.71]) and Fishermen, hunters and related workers (OR = 4.58 [1.33; 15.78]); whether overall and non-aggressive PCa, among Legislative officials and Government administrators (OR = 3.30 [1.10; 9.84]) or Managers (OR = 1.68 [1.18; 2.41]); however a negative association, whether overall and non-aggressive PCa, among Material-Handling and Related Equipment Operators, Dockers and Freight Handlers (OR = 0.40 [0.17; 0.97]).

Conclusion

Excess PCa risks were observed in the EPICAP study mostly among white collar workers exposed to several factors in their work environment. These emerging associations can be used to lead future research investigating specific occupational exposures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12995-022-00346-2.

PRNCR1: a long non-coding RNA with a pivotal oncogenic role in cancer

Long non-coding RNAs (lncRNAs) have been gaining importance in the field of cancer research in recent years. PRNCR1 (prostate cancer-associated non-coding RNA1) is a 12.7 kb, intron-less lncRNA found to play an oncogenic role in malignancy of diverse organs including prostate, breast, lung, oral cavity, colon and rectum. Single-nucleotide polymorphisms (SNPs) of PRNCR1 locus have been found to be associated with cancer susceptibility in different populations. In this review, an attempt has been made for the first time to summarize all sorts of available data on PRNCR1 to date from relevant databases (GeneCard, LncExpDB, Ensembl genome browser, and PubMed). As functional roles of PRNCR1, miRNA (microRNA) sponging was mostly highlighted in the pathogenesis of different cancer; in addition, an association of the lncRNA with chromatin-modifying complex to enhance androgen receptor-mediated gene transcription was reported in prostate cancer. Diagnostic and prognostic importance of PRNCR1 was found in some malignancies suggesting potency of the lncRNA to serve as a clinical biomarker. For PRNCR1 SNPs, although cancer susceptibility of the risk alleles/genotypes was reported in different populations, majorities of the findings were not replicated and underlying molecular mechanisms remained unexplored. Therapeutic implication of PRNCR1 was not studied well and future research may come up in this direction for intervening novel strategies to fight against cancer.

De Novo Radiomics Approach Using Image Augmentation and Features From T1 Mapping to Predict Gleason Scores in Prostate Cancer

OBJECTIVES

The aims of this study were to discriminate among prostate cancers (PCa's) with Gleason scores 6, 7, and ≥8 on biparametric magnetic resonance imaging (bpMRI) of the prostate using radiomics and to evaluate the added value of image augmentation and quantitative T1 mapping.

MATERIALS AND METHODS

Eighty-five patients with subsequently histologically proven PCa underwent bpMRI at 3 T (T2-weighted imaging, diffusion-weighted imaging) with 66 patients undergoing additional T1 mapping at 3 T. The PCa lesions as well as the peripheral and transition zones were segmented pixel by pixel in multiple slices of the 3D MRI data sets (T2-weighted images, apparent diffusion coefficient, and T1 maps). To increase the size of the data set, images were augmented for contrast, brightness, noise, and perspective multiple times, effectively increasing the sample size 10-fold, and 322 different radiomics features were extracted before and after augmentation. Four different machine learning algorithms, including a random forest (RF), stochastic gradient boosting (SGB), support vector machine (SVM), and k-nearest neighbor, were trained with and without features from T1 maps to differentiate among 3 different Gleason groups (6, 7, and ≥8).

RESULTS

Support vector machine showed the highest accuracy of 0.92 (95% confidence interval [CI], 0.62-1.00) for classifying the different Gleason scores, followed by RF (0.83; 95% CI, 0.52-0.98), SGB (0.75; 95% CI, 0.43-0.95), and k-nearest neighbor (0.50; 95% CI, 0.21-0.79). Image augmentation resulted in an average increase in accuracy between 0.08 (SGB) and 0.48 (SVM). Removing T1 mapping features led to a decline in accuracy for RF (-0.16) and SGB (-0.25) and a higher generalization error.

CONCLUSIONS

When data are limited, image augmentations and features from quantitative T1 mapping sequences might help to achieve higher accuracy and lower generalization error for classification among different Gleason groups in bpMRI by using radiomics.

Multi-Dimensional Scaling Analysis of Key Regulatory Genes in Prostate Cancer Using the TCGA Database

Prostate cancer (PC) is a polygenic disease with multiple gene interactions. Therefore, a detailed analysis of its epidemiology and evaluation of risk factors can help to identify more accurate predictors of aggressive disease. We used the transcriptome data from a cohort of 243 patients from the Cancer Genome Atlas (TCGA) database. Key regulatory genes involved in proliferation activity, in the regulation of stress, and in the regulation of inflammation processes of the tumor microenvironment were selected to test a priori multi-dimensional scaling (MDS) models and create a combined score to better predict the patients' survival and disease-free intervals. Survival was positively correlated with cortisol expression and negatively with Mini-Chromosome Maintenance 7 (MCM7) and Breast-Related Cancer Antigen2 (BRCA2) expression. The disease-free interval was negatively related to the expression of enhancer of zeste homolog 2 (EZH2), MCM7, BRCA2, and programmed cell death 1 ligand 1 (PD-L1). MDS suggested two separate pathways of activation in PC. Within these two dimensions three separate clusters emerged: (1) cortisol and brain-derived neurotrophic factor BDNF, (2) PD-L1 and cytotoxic-T-lymphocyte-associated protein 4 (CTL4); (3) and finally EZH2, MCM7, BRCA2, and c-Myc. We entered the three clusters of association shown in the MDS in several Kaplan-Meier analyses. It was found that only Cluster 3 was significantly related to the interval-disease free, indicating that patients with an overall higher activity of regulatory genes of proliferation and DNA repair had a lower probability to have a longer disease-free time. In conclusion, our data study provided initial evidence that selecting patients with a high grade of proliferation and DNA repair activity could lead to an early identification of an aggressive PC with a potentials for metastatic development.

Development and validation of a set of novel and robust 4-lncRNA-based nomogram predicting prostate cancer survival by bioinformatics analysis

Background and objective

Accumulating evidence shows that long noncoding RNAs (lncRNAs) possess great potential in the diagnosis and prognosis of prostate cancer (PCa). Therefore, this study aimed to construct an lncRNA-based signature to more accurately predict the prognosis of different PCa patients, so as to improve patient management and prognosis.

Methods

Through univariate and multivariate Cox regression analysis, this study constructed a 4 lncRNAs-based prognosis nomogram for the classification and prediction of survival risk in patients with PCa based on TCGA data. Then we used the data of TCGA and ICGC to verify the performance of our prediction model. The receiver operating characteristic curve was plotted for detecting and validating our prediction model sensitivity and specificity. In addition, Cox regression analysis was conducted to examine whether the signature’s prediction ability was independent of additional clinicopathological variables. Possible biological functions for those prognostic lncRNAs were predicted on those 4 protein-coding genes (PCGs) related to lncRNAs.

Results

Four lncRNAs (HOXB-AS3, YEATS2-AS1, LINC01679, PRRT3-AS1) were extracted after COX regression analysis for classifying patients into high and low-risk groups by different OS rates. As suggested by ROC analysis, our proposed model showed high sensitivity and specificity. Independent prognostic capability of the model from other clinicopathological factors was indicated through further analysis. Based on functional enrichment, those action sites for prognostic lncRNAs were mostly located in the extracellular matrix and cell membrane, and their functions are mainly associated with the adhesion, activation and transport of the components across the extracellular matrix or cell membrane.

Conclusion

Our current study successfully identifies a novel candidate, which can provide more convincing evidence for prognosis in addition to the traditional clinicopathological indicators to predict the PCa survival, and laying the foundation for offering potentially novel therapeutic treatment. Additionally, this study sheds more lights on the PCa-related molecular mechanisms.

Clinical Utility of Negative Multiparametric Magnetic Resonance Imaging in the Diagnosis of Prostate Cancer and Clinically Significant Prostate Cancer

Background

Multiparametric magnetic resonance imaging (MRI) is increasingly used to diagnose prostate cancer (PCa). It is not yet established whether all men with negative MRI (Prostate Imaging-Reporting and Data System version 2 score <3) should undergo prostate biopsy or not.

Objective

To develop and validate a prediction model that uses clinical parameters to reduce unnecessary prostate biopsies by predicting PCa and clinically significant PCa (csPCa) for men with negative MRI findings who are at risk of harboring PCa.

Design setting and participants

This was a retrospective analysis of 200 men with negative MRI at risk of PCa who underwent prostate biopsy (2014-2020) with prostate-specific antigen (PSA) >4 ng/ml, 4Kscore of >7%, PSA density ≥0.15 ng/ml/cm³, and/or suspicious digital rectal examination. The validation cohort included 182 men from another centre (University of Miami) with negative MRI who underwent systematic prostate biopsy with the same criteria.

Outcome measurements and statistical analysis

csPCa was defined as Gleason grade group ≥2 on biopsy. Multivariable logistic regression analysis was performed using coefficients of logit function for predicting PCa and csPCa. Nomogram validation was performed by calculating the area under receiver operating characteristic curves (AUC) and comparing nomogram-predicted probabilities with actual rates of PCa and csPCa.

Results and limitations

Of 200 men in the development cohort, 18% showed PCa and 8% showed csPCa on biopsy. Of 182 men in the validation cohort, 21% showed PCa and 6% showed csPCa on biopsy. PSA density, 4Kscore, and family history of PCa were significant predictors for PCa and csPCa. The AUC was 0.80 and 0.87 for prediction of PCa and csPCa, respectively. There was agreement between predicted and actual rates of PCa in the validation cohort. Using the prediction model at threshold of 40, 47% of benign biopsies and 15% of indolent PCa cases diagnosed could be avoided, while missing 10% of csPCa cases. The small sample size and number of events are limitations of the study.

Conclusions

Our prediction model can reduce the number of prostate biopsies among men with negative MRI without compromising the detection of csPCa.

Patient summary

We developed a tool for selection of men with negative MRI (magnetic resonance imaging) findings for prostate cancer who should undergo prostate biopsy. This risk prediction tool safely reduces the number of men who need to undergo the procedure.

Multiparametric MRI with in-bore targeted biopsy in the diagnostic pathway of prostate cancer: Data from a single institution experience

BACKGROUND

Accuracy of multiparametric MRI (mpMRI) for the detection of significant prostate cancer (CaP) varies in the literature as only few studies use radical prostatectomy specimens as their gold standard. On another hand, MRI-targeted prostate biopsy is emerging as an alternative to the traditional randomized biopsy, with a higher detection rate of high-grade cancers. However, data on MRI guided in bore biopsy is lacking.

MATERIAL AND METHODS

We reviewed every patient that had his mpMRI, MRI guided in bore biopsy and radical prostatectomy performed in our hospital between November 2015 and December 2020. The diagnostic performances of both mpMRI and MRI targeted biopsy in sampling PIRADS index lesions were studied, using radical prostatectomy specimens as the gold standard. Sensitivity, specificity, positive predictive value and negative predictive value of mpMRI for detecting T3 stage, extra-capsular extension, seminal vesicles involvement and lymph node disease were also evaluated.

RESULTS

Sixty-two met our inclusion criteria. For PIRADS≥3 lesions, sensitivity and positive predictive value for detecting clinically significant CaP were of 83.5% and 94.7%. A total of 32.2% prostate cancers on targeted biopsy were upgraded on final pathology, with an upgrading to ISUP≥2 in 3.2% and to ISUP≥3 in 14.5%. A total of 20.9% of cancers were downgraded but without any downgrading to ISUP 1. When final pathology is taken as a gold standard, sensitivity of mpMRI was 31.8% for T3 staging prediction, 30.0% for extra-capsular extension, 28.7% for seminal vesicles involvement and 66.7% for lymph node disease prediction. Specificity was 89.3%, 93.1%, 95.3%, and 92.7%, respectively.

CONCLUSION

mpMRI has an acceptable accuracy for the prediction of significant CaP and index lesion detection but is unreliable for CaP staging. Comparison between pathology and biopsy results revealed that the in-bore biopsy technique has an upgrading and downgrading rate comparable in the literature to fusion biopsy, but higher than the combined biopsy approach.

Gleason Grade Group Concordance between Preoperative Targeted Biopsy and Radical Prostatectomy Histopathologic Analysis: A Comparison Between In-Bore MRI-guided and MRI-Transrectal US Fusion Prostate Biopsies

Purpose

To determine and compare rates of grade group (GG) discrepancies between different targeted biopsy techniques (in-bore vs fusion) after propensity score weighting using whole-mount radical prostatectomy (RP) histopathologic analysis as the reference standard.

Materials and Methods

This retrospective study evaluated men who underwent targeted (fusion or in-bore) biopsy between April 2017 and January 2019 followed by prostatectomy. The primary endpoint of the study was a change in GG from biopsy to RP at a patient level. For downgrade and upgrade analysis, men with biopsy GG1 (downgrade not possible) and GG5 (upgrade not possible) were excluded, respectively. GG upgrade, downgrade, and concordance rates of each targeting approach were compared using propensity score weighting and logistic regression with inverse probability of treatment weighting. Significance level was set at .05. Index lesion GG on RP specimen served as the reference standard.

Results

A total of 191 men (90 in the in-bore [mean age, 63 years ± 7 (standard deviation)] and 101 in the fusion biopsy group [mean age, 65 years ± 7]) were eligible and included. Fewer GG upgrades were noted in the in-bore biopsy group (14%; 12 of 85) compared with the fusion plus systematic biopsy group (30%; 28 of 93) (P = .012). The incidence of GG downgrade in the in-bore group (25%; 21 of 84) was higher than in the fusion group (17%; 16 of 93); however, the difference was not statistically significant (P = .2). Of the 77 men misclassified by both biopsy techniques, the majority (56%, n = 43) had a change in GG of 2 to 3 or 3 to 2.

Conclusion

Superior sampling accuracy with MRI-guided in-bore biopsies offers a lower incidence of GG upgrades compared with MRI-transrectal US fusion biopsies upon RP.Keywords: Biopsy/Needle Aspiration, MR-Imaging, Oncology, Pathology, Prostate Supplemental material is available for this article.© RSNA, 2021.

Comparison of TRUS and combined MRI-targeted plus systematic prostate biopsy for the concordance between biopsy and radical prostatectomy pathology

AIM

To evaluate the accuracy in histologic grading of MRI/US image fusion biopsy by comparing conventional 12-core TRUS-Bx at radical prostatectomy specimens (RP).

METHODS

Consecutive patients diagnosed prostate cancer (127 with combination of both targeted biopsy (TBx) plus systematic biopsies (SBx) and separate patient cohort of 330 conventional TRUS-Bx without mpMRI) with a PSA level of <20 ng/mL prior to RP were included. The primary end point was the grade group concordance between biopsy and RP pathology according to biopsy technique.

RESULTS

Clinically significant prostate cancer detection was 51.2% for TRUS-Bx, 49.5% for SBx, 67% for TBx and 75.7% for TBx + SBx. Upgrading and downgrading of at least one Gleason Grade Group (GGG) was recorded in 43.3%/ 6.7% patients of the TRUS-Bx and in 20.5%/ 22% of the TBX + SBx group, respectively (all P < .001). Concordance level was detected to be significantly higher for ISUP 1 in combined TBx + SBx method compared to conventional TRUS-Bx (61.3% vs 37.9%, P = .014). In ISUP 1 exclusively, significant upgrading was seen in TRUS-Bx (62.1%) when compared to TBx (41.4%) and TBx + SBx (38.7%).

CONCLUSIONS

MRI-targeted biopsies detected more significant PCa than TRUS-Bx but, superiority in significant cancer detection appears as a result of inadvertant selective sampling of small higher grade areas. Within an otherwise low grade cancer and does not reflect accurate GGG final surgical pathology. TBx + SBx has the greatest concordance in ISUP Grade 1 with less upgrading which is utmost important for active surveillance.

Optimizing outcomes for patients with metastatic prostate cancer: insights from South East Asia Expert Panel

AIMS

Clinical decision making is challenging in men with metastatic prostate cancer (mPC), as heterogeneity in treatment options and patient characteristics have resulted in multiple scenarios with little or no evidence. The South East Asia Expert Panel 2019 addressed some of these challenges.

METHODS

Based on evidence in the literature and expert interviews, 19 statements were formulated for key challenges in the treatment of men with castration-sensitive and -resistant prostate cancer in clinical practice. A modified Delphi process was used to reach consensus among experts in the panel and develop clinical practice recommendations.

RESULTS

The majority of the panel preferred a risk-based stratification and recommended abiraterone or enzalutamide as first-line therapy for symptomatic chemotherapy naïve patients. Abiraterone is preferred over enzalutamide as a first-line treatment in these patients. However, the panel did not support the use of abiraterone in high risk lymph-node positive only (N+M0) or in non-metastatic (N0M0) patients. In select patients, low dose abiraterone with food may be used to optimize clinical outcomes. Androgen receptor gene splice variant status may be a useful guide to therapy. In addition, generic versions of approved therapies may improve access to treatment to a broader patient population. The choice of treatment, as well as sequencing are guided by both patient and disease characteristics, preferences, drug access, cost, and compliance.

CONCLUSION

Expert recommendations are key to guidance for the optimal management of mPC. Appropriate choice, timing, and sequence of treatment options can help to tailor therapy to maximize outcomes in men with mPC.

Opposing prognostic relevance of junction plakoglobin in distinct prostate cancer patient subsets

Both oncogenic and tumor suppressor functions have been described for junction plakoglobin (JUP), also known as γ-catenin. To clarify the role of JUP in prostate cancer, JUP protein expression was immunohistochemically detected in a tissue microarray containing 11 267 individual prostatectomy specimens. Considering all patients, high JUP expression was associated with adverse tumor stage (P = 0.0002), high Gleason grade (P < 0.0001), and lymph node metastases (P = 0.011). These associations were driven mainly by the subset without TMPRSS2:ERG fusion, in which high JUP expression was an independent predictor of poor prognosis (multivariate analyses, P = 0.0054) and early biochemical recurrence (P = 0.0003). High JUP expression was further linked to strong androgen receptor expression (P < 0.0001), high cell proliferation, and PTEN and FOXP1 deletion (P < 0.0001). In the ERG-negative subset, high JUP expression was additionally linked to MAP3K7 (P = 0.0007) and CHD1 deletion (P = 0.0021). Contrasting the overall prognostic effect of JUP, low JUP expression indicated poor prognosis in the fraction of CHD1-deleted patients (P = 0.039). In this subset, the association of high JUP and high cell proliferation was specifically absent. In conclusion, the controversial biological roles of JUP are reflected by antagonistic prognostic effects in distinct prostate cancer patient subsets.

Development of Mobile Application for Dynamically Monitoring the Risk of Prostate Cancer and Clinicopathology

OBJECTIVE

To develop an application dynamically monitoring the prostate cancer (PCa) risk for patients to assess their own progression of PCa risk at home.

METHODS

Between January 2010 and December 2019, all of the 1697 patients underwent transrectal ultrasound prostate biopsy at the cancer center, which is one of the Chinese Prostate Cancer Consortium. Patients' clinical parameters from January 2010 to May 2018 were used to establish models that consisted of several risk factors with P value <0.1 in univariate analysis and with P value <0.05 in multivariate analysis (n=1113), including model 1 (predicting PCa), model 2 (predicting PCa with high Gleason scores (7 or higher)) and model 3 (predicting PCa with the high clinical stage (T2b or higher)). Other patients from June 2018 to December 2019 were used to validate models (n=440). Patients with a lack of sufficient data were eventually excluded (n=144).

RESULTS

A total of 1553 patients were involved in this study, and an application was used to perform the models. The predictive cut-off value and area under the curves (AUCs) of model 1, 2 and 3 were, respectively, calculated (cut-off: 0.53, 0.38 and 0.40, AUCs: 0.88, 0.89 and 0.89). Using a cut-off value of 10%, three models obtained a high sensitivity (>95%). Besides, more patients can be correctly reclassified via our models (42.9 to 55.5%). Decision curve analyses revealed a decent net benefit in any probability for models. These results were well verified in the validation cohort.

CONCLUSION

This application showed decent performance in predicting the risk of PCa and clinicopathology, which was available and convenient for patients to self-assess the progress of PCa risks so that being better to participate in disease management.

Association between preoperative prostate-specific antigen levels and mortality in high- and intermediate-grade prostate cancer patients who received radical prostatectomy: Findings from the SEER database

Background

The degree of expression of prostate-specific antigen (PSA) has been applied for the purpose of screening and monitoring the progression of prostate cancer. The goal of this study was to evaluate the association between preoperative PSA levels and mortality outcomes in men with high- and intermediate-grade prostate cancer who received radical prostatectomy.

Methods

The 2004–2014 files of the Surveillance, Epidemiology, and End Result database were analyzed. A total of 97,357 patients with non-metastatic high- and intermediate-grade adenocarcinoma of the prostate who received radical prostatectomy were identified. Using Kaplan–Meier estimates and multivariable Cox proportional hazard models, the relationship between preoperative PSA values and cancer-specific mortality outcomes in men with high- and intermediate-grade prostate cancer who received radical prostatectomy was tested.

Results

Of 97,357 patients with high- and intermediate-grade prostate cancer who received radical prostatectomy from 2001 to 2014, there were 983 cancer-specific deaths, and the average follow-up time for the cohort was 85.0 (34.6) months. Preoperative PSA values > 10 ng/ml were associated with greater risk of cancer-specific mortality (hazard ratio 2.3, P < 0.0001) when compared to the referent/normal values for preoperative PSA (<4 ng/ml). Individuals with preoperative PSA values 4–10 ng/ml had lower risk of prostate cancer-specific mortality (hazard ratio 0.80, P = 0.03) when compared to individuals with normal preoperative PSA values.

Conclusions

Individuals with preoperative PSA values 4–10 ng/ml had 20% lower risk of prostate cancer-specific mortality when compared to individuals with preoperative PSA values of <4 ng/dl. The findings from this study suggest that low or normal preoperative PSA values may not always mean that prostate cancer is indolent, and more work needs to be done to better classify risk in men with prostate cancer.

Resetting the Bar of Castration Resistance - Understanding Androgen Dynamics in Therapy Resistance and Treatment Choice in Prostate Cancer

This review discusses impact of advancements in biologic understanding of prostate cancer (PCa) on definition and diagnosis of castration-resistant PCa (CRPC), predictive factors for progression to CRPC and treatment strategies. More sensitive assays confirm that bilateral orchiectomy reduces serum testosterone (T) closer to < 20 ng/dL than < 50 ng/dL, and evidence suggests that achieving T < 20 ng/dL improves outcomes and delays CRPC emergence. Regular T assessments will evaluate whether T is adequately suppressed in the setting of potential progression to CRPC, given that late dosing may result in T escape. More advanced imaging modalities and biomarker assays allow earlier detection of disease progression. Predictive factors for progression to CRPC include Gleason grade, extent of metastatic spread, germline hereditary factors such as gene mutations affecting androgen receptor amplification or DNA repair deficiency mutations, prostate-specific antigen kinetics, and biomarker analyses. Treatment options for CRPC have expanded beyond androgen deprivation therapy to include therapies that suppress T or inhibit its activity through varying mechanisms. Future directions include therapies with novel biological targets, drug combinations and personalized treatments. Advanced PCa management aims to delay progression to CRPC and prolong survival. With redefinition of castration and advancements in understanding of the biology of disease progression, diagnosis and treatment strategies should be re-evaluated. Definition of CRPC could be updated to reflect the T < 20 ng/dL requirement as this is a 'true' castrate level and may improve outcomes. It is important that androgen deprivation therapy as foundational therapy is continued even as new CRPC therapies are introduced.

Investigating association of perineural invasion on prostate biopsy with Gleason score upgrading at prostatectomy: A multi-institutional analysis

Background

The significance of perineural invasion (PNI) in prostate cancer (PC) is unclear. A recent report of patients with pT2N0R0 PC found that PNI at prostatectomy was independently associated with higher Gleason score and more diffuse prostatic disease. We aimed to test our hypothesis that PNI on prostate biopsy in pT2N0R0 patients is associated with increased Gleason score upgrading at prostatectomy.

Methods

We identified 2892 patients status post prostatectomy with pT2N0R0 PC from three institutions, diagnosed between 1 January 2008 and 31 December 2014. Multivariable logistic regression (MVA) was used to evaluate the association between prostate biopsy PNI status and surgical Gleason upgrading, while controlling for potential confounders.

Results

Of the 2892 patients identified, 14% had PNI on biopsy, of whom 21% had surgical Gleason upgrading, while 28% without PNI on biopsy had such upgrading (P < .01). On MVA, the odds ratio (OR) of surgical Gleason upgrading for patients with biopsy PNI relative to patients without biopsy PNI was 0.69 (P < .01). The variables associated with surgical Gleason upgrading were age ≤60 years (OR 1.22, P = .02) and preoperative PSA >4 ng/mL (OR 1.26, P = .02).

Conclusions

In post‐prostatectomy patients with favorable‐risk PC, PNI on prostate biopsy was not associated with surgical Gleason score upgrading. This may be due to the association of PNI with more diffuse disease, leading to increased biopsy tumor yield and grading accuracy. These findings suggest that in this setting, biopsy PNI alone should not be a concern for more aggressive disease requiring pathologic confirmation or intervention. This may help guide treatment decision‐making for men debating active surveillance, radiation, and surgery.

Diagnostic, prognostic and predictive parameters in prostate cancer

Prostate cancer (CP) is the most common malignancy in men in America, while it is the second most common in Europe. It is responsible for about 10% of cancer deaths in the same population. It is clinically manifested in various forms, from slow-growing to aggressive forms with pronounced metastatic potential. Diagnosis is made by a well-defined algorithm, which begins with the determination of serum prostate specific antigen values and ends with prostate biopsy as the "gold standard". Pathohistological diagnostic criterias are based on architectural, cytoplasmic, nuclear and characteristics of intraluminal structures, as well as periacinar cleftings, which are deffined as helpfull diagnostic criteria of undoubted importance. Prognostic and predictive parameters are classified into three categories. Some of them are an integral part of routine pathohistologicat report, while others are considered as the diagnostic process progresses. Modern knowledge introduces biomarkers into the everyday practice of personalized medicine, especially when is necessary to treat prostate cancer patients.

Pathological upgrading in prostate cancer treated with surgery in the United Kingdom: trends and risk factors from the British Association of Urological Surgeons Radical Prostatectomy Registry

BACKGROUND

Accurate grading at the time of diagnosis if fundamental to risk stratification and treatment decision making in patients with prostate cancer. Whilst previous studies have demonstrated significant pathological upgrading and downgrading following radical prostatectomy (RP), these were based on historical cohorts and do not reflect contemporary patient selection and management practices. The aim of this national, multicentre observational study was to characterise contemporary rates and risk factors for pathological upgrading after RP in the United Kingdom (UK).

METHODS

All RP entries on the British Association of Urological Surgeons (BAUS) Radical Prostatectomy Registry database of prospectively entered cases undertaken between January 2011 and December 2016 were extracted. Those patients with full preoperative PSA, clinical stage, needle biopsy and subsequent RP pathological grade information were included. Upgrade was defined as any increase in Gleason grade from initial needle biopsy to pathological assessment of the entire surgical specimen. Statistical analysis and multivariate logistic regression were undertaken using R version 3.5 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

A total of 17,598 patients met full inclusion criteria. Absolute concordance between initial biopsy and pathological grade was 58.9% (n = 10,364), whilst upgrade and downgrade rates were 25.5% (n = 4489) and 15.6% (n = 2745) respectively. Upgrade rate was highest in those with D'Amico low risk compared with intermediate and high-risk disease (55.7% versus 19.1 and 24.3% respectively, P < 0.001). Although rates varied between year of surgery and geographical regions, these differences were not significant after adjusting for other preoperative diagnostic variables using multivariate logistic regression.

CONCLUSIONS

Pathological upgrading after RP in the UK is lower than expected when compared with other large contemporary series, despite operating on a generally higher risk patient cohort. As new diagnostic techniques that may reduce rates of pathological upgrading become more widely utilised, this study provides an important benchmark against which to measure future performance.

Prognostic Significance for Long-Term Outcomes Following Radical Prostatectomy in Men with Prostate Cancer: Evaluation with Prostate Imaging Reporting and Data System Version 2

Objective

To retrospectively determine whether the use of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) helps predict long-term outcomes for prostate cancer (PCa) patients following radical prostatectomy (RP).

Materials and Methods

A total of 166 patients with localized PCa evaluated with multiparametric magnetic resonance imaging (mpMRI) at 3T before RP were enrolled. Three groups were created based on PI-RADS v2 score used to predict clinical outcomes: group A, ≥ 3; group B, ≥ 4; group C, 5. We calculated biochemical recurrence-free survival (RFS) and progression-free survival (PFS). Cox proportion hazards models were used to identify variables predictive of biochemical recurrence and disease progression.

Results

During a median follow-up of 9.1 years, biochemical recurrence occurred in 67 patients (40.4%) and disease progression occurred in 55 patients (33.1%). In all groups, 10-year RFS and 10-year PFS were significantly lower for PI-RADS scores ≥ 3, ≥ 4 and 5 than for score < 3, < 4 and < 5 (p <0.05), respectively. In multivariate analysis, PI-RADS score ≥ 3 and score 5 were significant independent risk marker for biochemical recurrence (hazard ratio [HR] = 5.58, p = 0.018; HR = 1.75, p = 0.033) and disease progression (HR = 3.99, p = 0.047; HR = 2.31, p = 0.040). Moderate inter-observer agreement was seen for PI-RADS scoring.

Conclusion

PI-RADS v2 may be used to predict long-term outcomes following RP in PCa.

Statistical Analysis of Survival Models Using Feature Quantification on Prostate Cancer Histopathological Images

BACKGROUND

Grading of prostatic adenocarcinoma is based on the Gleason scoring system and the more recently established prognostic grade groups. Typically, prostate cancer grading is performed by pathologists based on the morphology of the tumor on hematoxylin and eosin (H and E) slides. In this study, we investigated the histopathological image features with various survival models and attempted to study their correlations.

METHODS

Three texture methods (speeded-up robust features, histogram of oriented gradient, and local binary pattern) and two convolutional neural network (CNN)-based methods were applied to quantify histopathological image features. Five survival models were assessed on those image features in the context with other prostate clinical prognostic factors, including primary and secondary Gleason patterns, prostate-specific antigen levels, age, and clinical tumor stages.

RESULTS

Based on statistical comparisons among different image features with survival models, image features from CNN-based method with a recurrent neural network called CNN-long-short-term memory provided the highest hazard ratio of prostate cancer recurrence under Cox regression with an elastic net penalty.

CONCLUSIONS

This approach outperformed the other image quantification methods listed above. Using this approach, patient outcomes were highly correlated with the histopathological image features of the tissue samples. In future studies, we plan to investigate the potential use of this approach for predicting recurrence in a wider range of cancer types.

Concordance Between Biopsy and Radical Prostatectomy Pathology in the Era of Targeted Biopsy: A Systematic Review and Meta-analysis

CONTEXT

Multiparametric magnetic resonance imaging (mpMRI)-targeted transrectal prostate biopsy (TBx) may better predict pathology at radical prostatectomy than systematic transrectal prostate biopsy (SBx).

OBJECTIVE

To assess concordance between biopsy and radical prostatectomy pathology in men undergoing a TBx as compared with those undergoing an SBx.

EVIDENCE ACQUISITION

Four electronic databases (Ovid MEDLINE, Ovid EMBASE, the Cochrane Library [Wiley], and EBSCHOHost) were searched from inception until July 2018. Studies were included if they were published after 2012, conducted both SBx and TBx, and compared the biopsy results with final pathology after radical prostatectomy for ≥50 patients. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were utilized. Bias was appraised using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

EVIDENCE SYNTHESIS

Our search yielded 10 studies including 1215 men. However, our inclusion criteria applied only to a proportion of men included in these studies. The median age was 65 yr and the median prostate-specific antigen level was 7.2 ng/ml. In the eight studies examining upgrading at prostatectomy, pathology from SBx was significantly more likely to be upgraded relative to TBx (odds ratio [OR] 2.47, 95% confidence interval [CI] 1.48-4.14, p =  0.001). We found no significant difference in downgrading (OR 1.13, 95% CI 0.48-2.67, p =  0.783) between TBx and SBx. For both biopsy-naïve men and men with a prior negative biopsy, results from SBx were more likely to be upgraded than TBx at prostatectomy (OR 1.6 [95% CI 1.02-2.27, p <  0.001] and OR 4.23 [95% CI 1.68-8.48, p =  0.003], respectively).

CONCLUSIONS

Pathologic upgrading at prostatectomy was less likely with mpMRI-targeted biopsy versus systematic biopsy alone, without concurrent increase in downgrading. This increased accuracy should improve confidence in management decisions based on MRI-targeted biopsy pathology.

PATIENT SUMMARY

We reviewed the ability of multiparametric magnetic resonance imaging -targeted biopsy to predict cancer grade at radical prostatectomy. We found that targeted biopsy provides more accurate assessment of Gleason score at prostatectomy than systematic biopsy.

Development of biomarkers of genitourinary cancer using mass spectrometry-based clinical proteomics

Prostate, bladder and kidney cancer are the three most common types of genitourinary cancer in the world. Of these, prostate and bladder cancers are within the top 10 most common cancers in men. Notably, kidney cancer causes no obvious symptoms in the early stages. To satisfy clinical-management requirements, researchers have developed numerous biomarkers by applying proteomic approaches using clinical serum, urine and tissue specimens, as well as cell and animal models. Through application of biomarker pipeline protocols, including discovery, verification and validation phases, and mass-spectrometric based proteomic platforms coupled with multiplexed quantification assays, these studies have led to recent rapid progress in this area. With improvements in mass-spectrometric based proteomic techniques, numerous promising biomarker candidates and marker panels for various clinical purposes have been proposed. Verification of novel protein biomarker candidates is very resource demanding (e.g. on the clinical and laboratory sides). With the support of national consortia, it is now possible to investigate the future clinical use of such biomarker strategies and assess their cost-effectiveness in personalized medicine.

Circadian genes and risk of prostate cancer: Findings from the EPICAP study

Circadian rhythms regulate several physiological functions and genes controlling the circadian rhythm were found to regulate cell proliferation, cell cycle and apoptosis. Few studies have investigated the role of those circadian genes in prostate cancer occurrence. We aim to investigate the relationship between circadian genes polymorphisms and prostate cancer risk based on data from the EPICAP study, a population-based case-control study including 1,515 men (732 cases / 783 controls) with genotyped data. Odds Ratios (ORs) for association between prostate cancer and circadian gene variants were estimated for each of the 872 single nucleotide polymorphisms (SNPs) in 31 circadian clock genes. We also used a gene-based and pathway-based approach with a focus on the pathway including 9 core circadian genes. Separate analyses were conducted by prostate cancer aggressiveness. The core-circadian pathway (p = 0.0006) was significantly associated to prostate cancer, for either low (p = 0.002) or high (p = 0.01) grade tumor. At the gene level, we observed significant associations between all prostate cancer and NPAS2 and PER1 after correcting for multiple testing, while only RORA was significant for aggressive tumors. At the SNP-level, no significant association was observed. Our findings provide additional evidence of a potential link between genetic variants in circadian genes and prostate cancer risk. Further investigation is warranted to confirm these findings and to better understand the biological pathways involved.

Evolution, controversies and the future of prostate cancer grading

Histological grading of prostate cancer is one of the most important tissue-based parameters for prediction of outcome and treatment response. Gleason grading remains the foundation of prostate cancer grading, but has undergone a series of changes in the past 30 years, often initiated by consensus conference decisions. This review summarizes the most important modifications that were introduced by the 2005 and 2014 International Society of Urological Pathology (ISUP) revisions of Gleason grading and discusses the impact that these have had on current grading practices. A considerable inflation in Gleason scores has been observed, especially following the ISUP 2005 revision, and the effects of this are discussed. ISUP 2014 grading recommendations are described, including the reporting of ISUP grades 1-5. Controversial issues include methods for reporting of grades on needle biopsies, reporting of percent Gleason grades 4/5 and grading of cribriform and intraductal carcinoma of the prostate. Educational programs developed recently to promote standardization of grading are described and their results assessed.

Immunoreactivity for prostate specific antigen and Ki67 differentiates subgroups of prostate cancer related to outcome

Based on gene-expression profiles, prostate tumors can be subdivided into subtypes with different aggressiveness and response to treatment. We investigated if similar clinically relevant subgroups can be identified simply by the combination of two immunohistochemistry markers: one for tumor cell differentiation (prostate specific antigen, PSA) and one for proliferation (Ki67). This was analyzed in men with prostate cancer diagnosed at transurethral resection of the prostate 1975-1991 (n = 331) where the majority was managed by watchful waiting. Ki67 and PSA immunoreactivity was related to outcome and to tumor characteristics previously associated with prognosis. Increased Ki67 and decreased PSA were associated with poor outcome, and they provided independent prognostic information from Gleason score. A combinatory score for PSA and Ki67 immunoreactivity was produced using the median PSA and Ki67 levels as cut-off (for Ki67 the upper quartile was also evaluated) for differentiation into subgroups. Patients with PSA low/Ki67 high tumors showed higher Gleason score, more advanced tumor stage, and higher risk of prostate cancer death compared to other patients. Their tumor epithelial cells were often ERG positive and expressed higher levels of ErbB2, phosphorylated epidermal growth factor receptor (pEGF-R) and protein kinase B (pAkt), and their tumor stroma showed a reactive response with type 2 macrophage infiltration, high density of blood vessels and hyaluronic acid, and with reduced levels of caveolin-1, androgen receptors, and mast cells. In contrast, men with PSA high/Ki67 low tumors were characterized by low Gleason score, and the most favorable outcome amongst PSA/Ki67-defined subgroups. Men with PSA low/Ki67 low tumors showed clinical and tumor characteristics intermediate of the two groups above. A combinatory PSA/Ki67 immunoreactivity score identifies subgroups of prostate cancers with different epithelial and stroma phenotypes and highly different outcome but the clinical usefulness of this approach needs to be validated in other cohorts.

Racial Disparities in the Presentation, Early Definitive Surgical Treatment, and Mortality Among Men Diagnosed with Poorly Differentiated/Undifferentiated Non-metastatic Prostate Cancer in the USA

OBJECTIVE

To assess the influence of race on presentation of poorly differentiated/undifferentiated prostate cancer, use of radical prostatectomy (RP) as primary treatment and survival outcomes.

METHODS

Using the 2004-2014 files of the Surveillance, Epidemiology, and End Results (SEER) data, we identified 244,167 black and white men diagnosed with poorly differentiated/undifferentiated prostate cancer. Demographic and tumor characteristics of study patients were compared by race. Logistic regression was used to evaluate the influence of race on receipt of RP. Cox proportional hazard models were fitted to determine the impact of RP and race on cancer-specific mortality (CSM) and all-cause mortality (ACM).

RESULTS

Compared to white men, black men were diagnosed of prostate cancer at a younger age (64.2 years versus (vs) 67.5 years, p < 0.0001) and presented with higher median prostate-specific antigen, PSA (24.4 ng/ml vs 22.1 ng/ml, p < 0.0001) but lower disease stage. Lower proportion of black men received RP compared to white men (33.9% vs 42.6%; p < 0.0001). The odds of receipt of RP were 2 times higher in white men relative to black men. The risks of CSM and ACM were over 2 times and 3 times respectively higher in patients who did not receive RP vs patients who received RP in the study population and in each race.

CONCLUSION

Despite the younger age at diagnosis of poorly differentiated/undifferentiated prostate cancer and higher PSA at diagnosis in black men, white men had significantly higher odds of receipt of RP relative to black men.

Association between serum levels of insulin-like growth factor-1, bioavailable testosterone, and pathologic Gleason score

BACKGROUND

We evaluated the association between serum levels of insulin-like growth factor-1 (IGF-1), bioavailable testosterone, and surgical Gleason score (GS).

METHODS

We analyzed 793 patients who underwent radical prostatectomy and 272 men with negative prostate biopsy. Serum levels of IGF-1 and testosterone were measured before surgery or biopsy.

RESULTS

The mean IGF-1 levels of prostate cancer patients and men with a negative biopsy were 143.8 and 118.9 ng/mL, respectively (P < 0.001). Men with high serum IGF-1 were more likely to have prostate cancer (highest vs lowest quartile, odds ratio [OR] = 3.35; Ptrend  < 0.001). However, among men with prostate cancer, the mean IGF-1 levels of those with low (GS ≤ 6), intermediate (GS = 7), and high surgical GS (GS ≥8) were 151.7, 144.1, and 132.9 ng/mL, respectively (P < 0.001). Using quartile analysis, high serum IGF-1 levels were shown to be associated with a low risk of high surgical GS (OR = 0.464; Ptrend  = 0.006). Serum bioavailable testosterone concentration was positively correlated with serum IGF-1 level (r = 0.157, P < 0.001). High bioavailable testosterone level was also associated with a low risk of high surgical GS in patients without diabetes mellitus (OR = 0.569; Ptrend  = 0.040). Among men with biopsy GS ≤ 3 + 4 (n = 460), upgrading to high surgical GS was more frequent in patients with low IGF-1 level (≤116.0 ng/mL; 9.9%) or low bioavailable testosterone level (≤0.85 ng/mL; 9.3%) than in patients with normal IGF-1 and bioavailable testosterone levels (2.6%; P = 0.004).

CONCLUSIONS

Serum levels of IGF-1 and bioavailable testosterone show inverse associations with high surgical GS. This suggests that high-grade prostate cancer develops independently of these two substances.