Grading of prostatic adenocarcinoma: current state and prognostic implications

The number of involved regions by prostate adenocarcinoma predicts histopathology concordance between radical prostatectomy specimens and MRI/ultrasound-fusion targeted prostate biopsy

Introduction

The prostate biopsy (PB) results should be concordant with prostatectomy histopathology to avoid overestimating or underestimating the disease, leading to inappropriate or undertreatment of prostate cancer (PCa) patients. Since the introduction of multiparametric Magnetic Resonance Imaging (mpMRI) in the diagnostic pathway of PCa, most studies have shown that MRI/Ultrasound fusion-guided (MRI-fusion) PB improves concordance with histopathology of radical prostatectomy specimens. This study aimed to evaluate the improvement in concordance of prostatectomy specimens with PB histopathology obtained using the MRI-fusion approach compared with the 12-core TRUS-Bx and to identify the variables influencing this.

Patients and methods

The study included 218 men who were diagnosed with PCa by PB and underwent radical prostatectomy between 2016 and 2023. The patients were grouped based on the biopsy method: 115 underwent TRUS-Bx, and 103 underwent MRI-fusion PB. The histopathological grading of these biopsy approaches was compared with that of radical prostatectomy specimens. Multivariate logistic regression analyses were conducted to evaluate the impact of various criteria on histopathological concordance.

Results

In patients with unfavorable intermediate- and high-risk PCa, MRI-fusion PB showed significantly better concordance with prostatectomy histopathology than TRUS-Bx (73.1% vs. 42.9%, p = 0.018). MRI-fusion PB had a significantly lower downgrading of prostatectomy histopathology than TRUS-Bx in all grade categories. The number of cancer-involved regions of the prostate is an independent predictor for concordance (OR = 1.24, 95%CI = 1.04-1.52, p = 0.02) and downgrading (OR = 0.46, 95%CI = 0.24-0.83, p = 0.01).

Conclusions

Using an MRI-fusion PB improves histopathological concordance in patients with unfavorable intermediate and high-risk PCa. It reduces the downgrading rate of prostatectomy histopathology compared with TRUS-Bx in all grade categories. The number of cancer-involved regions is an independent predictor of the concordance between biopsy and final histopathology after prostatectomy and post-prostatectomy histopathology downgrading. Our findings could assist in selecting PCa patients for AS and focal treatment based on the histopathology obtained from the MRI-fusion PB.

Validation and three years of clinical experience in using an artificial intelligence algorithm as a second read system for prostate cancer diagnosis-real-world experience

Background

Prostate cancer ranks as the most frequently diagnosed cancer in men in the USA, with significant mortality rates. Early detection is pivotal for optimal patient outcomes, providing increased treatment options and potentially less invasive interventions. There remain significant challenges in prostate cancer histopathology, including the potential for missed diagnoses due to pathologist variability and subjective interpretations.

Methods

To address these challenges, this study investigates the ability of artificial intelligence (AI) to enhance diagnostic accuracy. The Galen™ Prostate AI algorithm was validated on a cohort of Puerto Rican men to demonstrate its efficacy in cancer detection and Gleason grading. Subsequently, the AI algorithm was integrated into routine clinical practice during a 3-year period at a CLIA certified precision pathology laboratory.

Results

The Galen™ Prostate AI algorithm showed a 96.7% (95% CI 95.6-97.8) specificity and a 96.6% (95% CI 93.3-98.8) sensitivity for prostate cancer detection and 82.1% specificity (95% CI 73.9-88.5) and 81.1% sensitivity (95% CI 73.7-87.2) for distinction of Gleason Grade Group 1 from Grade Group 2+. The subsequent AI integration into routine clinical use examined prostate cancer diagnoses on >122,000 slides and 9200 cases over 3 years and had an overall AI Impact ™ factor of 1.8%.

Conclusions

The potential of AI to be a powerful, reliable, and effective diagnostic tool for pathologists is highlighted, while the AI Impact™ in a real-world setting demonstrates the ability of AI to standardize prostate cancer diagnosis at a high level of performance across pathologists.

Heterogeneous genetic architectures of prostate cancer susceptibility in sub-Saharan Africa

Men of African descent have the highest prostate cancer incidence and mortality rates, yet the genetic basis of prostate cancer in African men has been understudied. We used genomic data from 3,963 cases and 3,509 controls from Ghana, Nigeria, Senegal, South Africa and Uganda to infer ancestry-specific genetic architectures and fine-map disease associations. Fifteen independent associations at 8q24.21, 6q22.1 and 11q13.3 reached genome-wide significance, including four new associations. Intriguingly, multiple lead associations are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of prostate cancer differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African prostate cancer associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.

Artificial Intelligence Algorithms and Their Current Role in the Identification and Comparison of Gleason Patterns in Prostate Cancer Histopathology: A Comprehensive Review

The development of the Gleason grading system has proven to be an irreplaceable tool in prostate cancer diagnostics within urology. Despite the advancements and developments in diagnostics, there remains a discrepancy in the grading process among even the most experienced pathologists. AI algorithms have demonstrated potential in detecting cancer and assigning Gleason grades, offering a solution to the issue of significant variability among pathologists' evaluations. Our paper explores the evolving role of AI in prostate cancer histopathology, with a key focus on outcomes and the reliability of various AI algorithms for Gleason pattern assessment. We conducted a non-systematic review of the published literature to examine the role of artificial intelligence in Gleason pattern diagnostics. The PubMed and Google Scholar databases were searched to gather pertinent information about recent advancements in artificial intelligence and their impact on Gleason patterns. We found that AI algorithms are increasingly being used to identify Gleason patterns in prostate cancer, with recent studies showing promising advancements that surpass traditional diagnostic methods. These findings highlight AI's potential to be integrated into clinical practice, enhancing pathologists' workflows and improving patient outcomes. The inter-observer variability in Gleason grading has seen an improvement in efficiency with the implementation of AI. Pathologists using AI have reported successful outcomes, demonstrating its effectiveness as a supplementary tool. While some refinements are still needed before AI can be fully implemented in clinical practice, its positive impact is anticipated soon.

Evaluation of Machine Learning Classification Models for False-Positive Reduction in Prostate Cancer Detection Using MRI Data

In this work, several machine learning (ML) algorithms, both classical ML and modern deep learning, were investigated for their ability to improve the performance of a pipeline for the segmentation and classification of prostate lesions using MRI data. The algorithms were used to perform a binary classification of benign and malignant tissue visible in MRI sequences. The model choices include support vector machines (SVMs), random decision forests (RDFs), and multi-layer perceptrons (MLPs), along with radiomic features that are reduced by applying PCA or mRMR feature selection. Modern CNN-based architectures, such as ConvNeXt, ConvNet, and ResNet, were also evaluated in various setups, including transfer learning. To optimize the performance, different approaches were compared and applied to whole images, as well as gland, peripheral zone (PZ), and lesion segmentations. The contribution of this study is an investigation of several ML approaches regarding their performance in prostate cancer (PCa) diagnosis algorithms. This work delivers insights into the applicability of different approaches for this context based on an exhaustive examination. The outcome is a recommendation or preference for which machine learning model or family of models is best suited to optimize an existing pipeline when the model is applied as an upstream filter.

A resource-based mechanistic framework for castration-resistant prostate cancer (CRPC)

Cancer therapy often leads to the selective elimination of drug-sensitive cells from the tumour. This can favour the growth of cells resistant to the therapeutic agent, ultimately causing a tumour relapse. Castration-resistant prostate cancer (CRPC) is a well-characterised instance of this phenomenon. In CRPC, after systemic androgen deprivation therapy (ADT), a subset of drug-resistant cancer cells autonomously produce testosterone, thus enabling tumour regrowth. A previous theoretical study has shown that such a tumour relapse can be delayed by inhibiting the growth of drug-resistant cells using biotic competition from drug-sensitive cells. In this context, the centrality of resource dynamics to intra-tumour competition in the CRPC system indicates clear scope for the construction of theoretical models that can explicitly incorporate the underlying mechanisms of tumour ecology. In the current study, we use a modified logistic framework to model cell-cell interactions in terms of the production and consumption of resources. Our results show that steady state composition of CRPC can be understood as a composite function of the availability and utilisation efficiency of two resources-oxygen and testosterone. In particular, we show that the effect of changing resource availability or use efficiency is conditioned by their general abundance regimes. Testosterone typically functions in trace amounts and thus affects steady state behaviour of the CRPC system differently from oxygen, which is usually available at higher levels. Our data thus indicate that explicit consideration of resource dynamics can produce novel and useful mechanistic understanding of CRPC. Furthermore, such a modelling approach also incorporates variables into the system's description that can be directly measured in a clinical context. This is therefore a promising avenue of research in cancer ecology that could lead to therapeutic approaches that are more clearly rooted in the biology of CRPC.

Grading pancreatic adenocarcinomas on fine needle aspiration cytology. The outstanding issues

OBJECTIVE

The three-tier grading scheme described in "The Papanicolaou Society of Cytopathology (PSC) System for reporting Pancreaticobiliary Cytopathology" (TPSCRPBC) which remained unchanged following the WHO Reporting System for Pancreaticobiliary Cytopathology (WRPBC) was evaluated on pancreatic adenocarcinomas (PACs) reported on endoscopic ultrasound-guided fine needle aspiration cytology (EUS-FNAC).

METHODS

The Papanicolaou and May Grunwald Giemsa-stained smears from 116 cases of PACs were graded using the three-tier grading scheme laid down by TPSCRPBC/WRPBC. Cases exhibiting multiple grades were assigned primary, secondary and tertiary grades. Each case was assigned a grade score, either by adding the primary and secondary grades, by adding the primary and tertiary grades when the tertiary grade was 3 or by doubling the grade when only one grade existed. Necrosis was estimated semi-quantitatively. The inter-observer reproducibility in grading was evaluated using Kappa and Kendall's tau-c. Correlations between the various grades, the stage of the tumour and the amount of necrosis were assessed using Spearman rho and Kendall's tau-b.

RESULTS

31.89% of cases showed one grade, and 68.11% showed at least two grades. 16.38% showed three grades. The two commonest grade scores were 3 and 5. The inter-observer reproducibility for grading and grade scoring was satisfactory. A positive correlation was noted between the grades and the amount of necrosis. No significant correlation was found between the grades, grade scores and the stage of the tumours.

CONCLUSIONS

The TPSCRPBC/WRPBC grading scheme can be suitably applied to PACs with good inter-observer reproducibility. Cases often show multiple grades in the same tumour.

Germline determinants of aberrant signaling pathways in cancer

Cancer is a complex disease influenced by a heterogeneous landscape of both germline genetic variants and somatic aberrations. While there is growing evidence suggesting an interplay between germline and somatic variants, and a substantial number of somatic aberrations in specific pathways are now recognized as hallmarks in many well-known forms of cancer, the interaction landscape between germline variants and the aberration of those pathways in cancer remains largely unexplored. Utilizing over 8500 human samples across 33 cancer types characterized by TCGA and considering binary traits defined using a large collection of somatic aberration profiles across ten well-known oncogenic signaling pathways, we conducted a series of GWAS and identified genome-wide and suggestive associations involving 276 SNPs. Among these, 94 SNPs revealed cis-eQTL links with cancer-related genes or with genes functionally correlated with the corresponding traits' oncogenic pathways. GWAS summary statistics for all tested traits were then used to construct a set of polygenic scores employing a customized computational strategy. Polygenic scores for 24 traits demonstrated significant performance and were validated using data from PCAWG and CCLE datasets. These scores showed prognostic value for clinical variables and exhibited significant effectiveness in classifying patients into specific cancer subtypes or stratifying patients with cancer-specific aggressive phenotypes. Overall, we demonstrate that germline genetics can describe patients' genetic liability to develop specific cancer molecular and clinical profiles.

Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole-genome sequencing with histopathological features

BACKGROUND

Extension of prostate cancer beyond the primary site by local invasion or nodal metastasis is associated with poor prognosis. Despite significant research on tumour evolution in prostate cancer metastasis, the emergence and evolution of cancer clones at this early stage of expansion and spread are poorly understood. We aimed to delineate the routes of evolution and cancer spread within the prostate and to seminal vesicles and lymph nodes, linking these to histological features that are used in diagnostic risk stratification.

METHODS

We performed whole-genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and lymph nodes of five treatment-naive patients with locally advanced disease. We spatially mapped the clonal composition of cancer across the prostate and the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes in each individual by analysing a total of > 19,000 copy number corrected single nucleotide variants.

RESULTS

In each patient, we identified sample locations corresponding to the earliest part of the malignancy. In patient 10, we mapped the spread of cancer from the apex of the prostate to the seminal vesicles and identified specific genomic changes associated with the transformation of adenocarcinoma to amphicrine morphology during this spread. Furthermore, we show that the lymph node metastases in this patient arose from specific cancer clones found at the base of the prostate and the seminal vesicles. In patient 15, we observed increased mutational burden, altered mutational signatures and histological changes associated with whole genome duplication. In all patients in whom histological heterogeneity was observed (4/5), we found that the distinct morphologies were located on separate branches of their respective evolutionary trees.

CONCLUSIONS

Our results link histological transformation with specific genomic alterations and phylogenetic branching. These findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes causally linked to morphological transformation. Our study demonstrates the value of integrating multi-region sequencing with histopathological data to understand tumour evolution and identify mechanisms of prostate cancer spread.

Transfer Learning with Pretrained Convolutional Neural Network for Automated Gleason Grading of Prostate Cancer Tissue Microarrays

Background

The Gleason grading system has been the most effective prediction for prostate cancer patients. This grading system provides this possibility to assess prostate cancer's aggressiveness and then constitutes an important factor for stratification and therapeutic decisions. However, determining Gleason grade requires highly-trained pathologists and is time-consuming and tedious, and suffers from inter-pathologist variability. To remedy these limitations, this paper introduces an automatic methodology based on transfer learning with pretrained convolutional neural networks (CNNs) for automatic Gleason grading of prostate cancer tissue microarray (TMA).

Methods

Fifteen pretrained (CNNs): Efficient Nets (B0-B5), NasNetLarge, NasNetMobile, InceptionV3, ResNet-50, SeResnet 50, Xception, DenseNet121, ResNext50, and inception_resnet_v2 were fine-tuned on a dataset of prostate carcinoma TMA images. Six pathologists separately identified benign and cancerous areas for each prostate TMA image by allocating benign, 3, 4, or 5 Gleason grade for 244 patients. The dataset was labeled by these pathologists and majority vote was applied on pixel-wise annotations to obtain a unified label.

Results

Results showed the NasnetLarge architecture is the best model among them in the classification of prostate TMA images of 244 patients with accuracy of 0.93 and area under the curve of 0.98.

Conclusion

Our study can act as a highly trained pathologist to categorize the prostate cancer stages with more objective and reproducible results.

Predictive significance of inflammatory markers and mGPS in metastatic castration-resistant prostate cancer treated with abiraterone or enzalutamide

BACKGROUND

Prostate cancer is a prevalent cancer in men worldwide, and castration-resistant prostate cancer (CRPC) is characterized by disease progression despite androgen deprivation therapy. While clinical and prognostic biomarkers have been identified in CRPC, the significance of serum inflammatory markers remains unclear.

MATERIALS AND METHODS

This retrospective study included 79 CRPC patients treated with abiraterone or enzalutamide. Inflammatory markers, including the modified Glasgow prognostic score (mGPS), systemic immune-inflammation index (SII), and neutrophil-to-lymphocyte ratio (NLR), were assessed as predictive tools for treatment response. Patient data were obtained from medical charts, and statistical analyses were performed.

RESULTS

The median age of the patients was 67 years, with most having a Gleason score of 8-10. The median values for NLR, PLR, and SII were 2.9, 168.5, and 713.5, respectively. The objective response rate (ORR) to abiraterone or enzalutamide therapy was 55.1%. mGPS showed a significant association with ORR, with the mGPS 0 group having the highest response rate (59.5%). Median progression-free survival (PFS) was 12.8 months, and median overall survival (OS) was 35.4 months. Palliative radiotherapy during therapy and PSA doubling time were independent prognostic factors for PFS.

CONCLUSIONS

mGPS and PSA doubling time significantly impacted survival, and mGPS significantly predicted the treatment response in mCRPC, which may lead to further prospective studies.

Comprehensive analysis of the impact of emerging flame retardants on prostate cancer progression: The potential molecular mechanisms and immune infiltration landscape

Emerging flame retardants have been used to replace traditional flame retardants, but their potential impact on cancer, especially prostate cancer, is not well understood. Our study aimed to explore the link between flame retardants and prostate cancer, and identify potential carcinogenic mechanisms among populations exposed to emerging flame retardants. We screened flame retardant interacting genes differentially expressed in prostate cancer patients and identified hub genes by protein-protein interaction (PPI) analysis based on the STRING database. Univariate and multivariate Cox regression analyses were performed to construct risk models and identify flame retardant-related prognostic genes. We calculated the proportion of immune cell infiltration to explore the potential mechanism of the prognostic gene, and verified the target cell population of the prognostic gene in the single-cell transcriptome dataset. Our study revealed a significant link between emerging flame retardants and prostate cancer. We constructed a risk model with good predictive ability for prostate cancer prognosis using TCGA dataset, and identified six flame retardant-related prognostic genes validated in the GSE70769 dataset. We found that the expression of M2 macrophages was up-regulated in patients with high expression of prognostic genes, and the single-cell dataset confirmed the expression of prognostic genes in macrophages. Our study confirms the link between emerging flame retardants and prostate cancer, and highlights the role of immune-related pathways in the high-risk population exposed to these flame retardants.

IQGAP3 is relevant to prostate cancer: A detailed presentation of potential pathomechanisms

INTRODUCTION

IQGAP3 possesses oncogenic actions; its impact on prostate cancer (PC) remains unclear.

OBJECTIVE

We will investigate IQGAP3's association with PC progression, key mechanisms, prognosis, and immune evasion.

METHODS

IQGAP3 expression in PC was examined by immunohistochemistry and using multiple datasets. IQGAP3 network was analyzed for pathway alterations and used to construct a multigene signature (SigIQGAP3NW). SigIQGAP3NW was characterized using LNCaP cell-derived castration-resistant PCs (CRPCs), analyzed for prognostic value in 26 human cancer types, and studied for association with immune evasion.

RESULTS

Increases in IQGAP3 expression associated with PC tumorigenesis, tumor grade, metastasis, and p53 mutation. IQGAP3 correlative genes were dominantly involved in mitosis. IQGAP3 correlated with PLK1 and TOP2A expression at Spearman correlation/R = 0.89 (p ≤ 3.069e-169). Both correlations were enriched in advanced PCs and Taxane-treated CRPCs and occurred at high levels (R > 0.8) in multiple cancer types. SigIQGAP3NW effectively predicted cancer recurrence and poor prognosis in independent PC cohorts and across 26 cancer types. SigIQGAP3NW stratified PC recurrence after adjustment for age at diagnosis, grade, stage, and surgical margin. SigIQGAP3NW component genes were upregulated in PC, metastasis, LNCaP cell-produced CRPC, and showed an association with p53 mutation. SigIQGAP3NW correlated with immune cell infiltration, including Treg in PC and other cancers. RELT, a SigIQGAP3NW component gene, was associated with elevations of multiple immune checkpoints and the infiltration of Treg and myeloid-derived suppressor cells in PC and across cancer types. RELT and SigIQGAP3NW predict response to immune checkpoint blockade (ICB) therapy.

CONCLUSIONS

In multiple cancers, IQGAP3 robustly correlates with PLK1 and TOP2A expression, and SigIQGAP3NW and/or RELT effectively predict mortality risk and/or resistance to ICB therapy. PLK1 and TOP2A inhibitors should be investigated for treating cancers with elevated IQGAP3 expression. SigIQGAP3NW and/or RELT can be developed for clinical applications in risk stratification and management of ICB therapy.

The grade of individual prostate cancer lesions predicted by magnetic resonance imaging and positron emission tomography

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) and positron emission tomography (PET) are widely used for the management of prostate cancer (PCa). However, how these modalities complement each other in PCa risk stratification is still largely unknown. We aim to provide insights into the potential of mpMRI and PET for PCa risk stratification.

METHODS

We analyzed data from 55 consecutive patients with elevated prostate-specific antigen and biopsy-proven PCa enrolled in a prospective study between December 2016 and December 2019. [68Ga]PSMA-11 PET (PSMA-PET), [11C]Acetate PET (Acetate-PET) and mpMRI were co-registered with whole-mount histopathology. Lower- and higher-grade lesions were defined by International Society of Urological Pathology (ISUP) grade groups (IGG). We used PET and mpMRI data to differentiate between grades in two cases: IGG 3 vs. IGG 2 (case 1) and IGG ≥ 3 vs. IGG ≤ 2 (case 2). The performance was evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

We find that the maximum standardized uptake value (SUVmax) for PSMA-PET achieves the highest area under the ROC curve (AUC), with AUCs of 0.72 (case 1) and 0.79 (case 2). Combining the volume transfer constant, apparent diffusion coefficient and T2-weighted images (each normalized to non-malignant prostatic tissue) results in AUCs of 0.70 (case 1) and 0.70 (case 2). Adding PSMA-SUVmax increases the AUCs by 0.09 (p < 0.01) and 0.12 (p < 0.01), respectively.

CONCLUSIONS

By co-registering whole-mount histopathology and in-vivo imaging we show that mpMRI and PET can distinguish between lower- and higher-grade prostate cancer, using partially discriminative cut-off values.

Renal Function Parameters in Distinctive Molecular Subtypes of Prostate Cancer

Prostate cancer is a prevalent malignancy in male patients, having diverse clinical outcomes. The follow-up of patients diagnosed with prostate cancer involves the evaluation of renal function, because its impairment reduces patient survival rates and adds complexity to their treatment and clinical care. This study aimed to investigate the relationship between renal function parameters and distinctive molecular subtypes of prostate adenocarcinomas, defined by the immunoexpression of the SPINK1, ERG, HOXB13, and TFF3 markers. The study group comprised 72 patients with prostate cancer and associated chronic kidney disease (CKD) who underwent radical prostatectomy. Histopathological, molecular, and renal parameters were analyzed. Patients were categorized based on ERG/SPINK1 and HOXB13/TFF3 status, and correlations with renal function and prognostic grade groups were assessed. The ERG+/SPINK1+ subgroup exhibited significantly higher postoperative CKD stages and serum creatinine levels compared to the ERG+/SPINK1- subgroup. This suggests an intricate relationship between SPINK1 overexpression and renal function dynamics. The HOXB13-/TFF3+ subgroup displayed higher preoperative serum creatinine levels and CKD stages than the HOXB13-/TFF3- subgroup, aligning with TFF3's potential role in renal function. Furthermore, the study revealed associations between CKD stages and prognostic grade groups in different molecular subtypes, pointing out an intricate interplay between renal function and tumor behavior. Although the molecular classification of prostate acinar ADK is not yet implemented, this research underscores the variability of renal function parameters in different molecular subtypes, offering potential insights into patient prognosis.

Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in Sub-Saharan Africa

Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.

Multi-model sequential analysis of MRI data for microstructure prediction in heterogeneous tissue

We propose a general method for combining multiple models to predict tissue microstructure, with an exemplar using in vivo diffusion-relaxation MRI data. The proposed method obviates the need to select a single 'optimum' structure model for data analysis in heterogeneous tissues where the best model varies according to local environment. We break signal interpretation into a three-stage sequence: (1) application of multiple semi-phenomenological models to predict the physical properties of tissue water pools contributing to the observed signal; (2) from each Stage-1 semi-phenomenological model, application of a tissue microstructure model to predict the relative volumes of tissue structure components that make up each water pool; and (3) aggregation of the predictions of tissue structure, with weightings based on model likelihood and fractional volumes of the water pools from Stage-1. The multiple model approach is expected to reduce prediction variance in tissue regions where a complex model is overparameterised, and bias where a model is underparameterised. The separation of signal characterisation (Stage-1) from biological assignment (Stage-2) enables alternative biological interpretations of the observed physical properties of the system, by application of different tissue structure models. The proposed method is exemplified with human prostate diffusion-relaxation MRI data, but has potential application to a wide range of analyses where a single model may not be optimal throughout the sampled domain.

Recent advances and future perspectives in the therapeutics of prostate cancer

Prostate cancer (PC) is one of the most common cancers in males and the fifth leading reason of death. Age, ethnicity, family history, and genetic defects are major factors that determine the aggressiveness and lethality of PC. The African population is at the highest risk of developing high-grade PC. It can be challenging to distinguish between low-risk and high-risk patients due to the slow progression of PC. Prostate-specific antigen (PSA) is a revolutionary discovery for the identification of PC. However, it has led to an increase in over diagnosis and over treatment of PC in the past few decades. Even if modifications are made to the standard PSA testing, the specificity has not been found to be significant. Our understanding of PC genetics and proteomics has improved due to advances in different fields. New serum, urine, and tissue biomarkers, such as PC antigen 3 (PCA3), have led to various new diagnostic tests, such as the prostate health index, 4K score, and PCA3. These tests significantly reduce the number of unnecessary and repeat biopsies performed. Chemotherapy, radiotherapy, and prostatectomy are standard treatment options. However, newer novel hormone therapy drugs with a better response have been identified. Androgen deprivation and hormonal therapy are evolving as new and better options for managing hormone-sensitive and castration-resistant PC. This review aimed to highlight and discuss epidemiology, various risk factors, and developments in PC diagnosis and treatment regimens.

Fibroblast-derived exosomal microRNA regulates NKX3-1 expression in androgen-sensitive, androgen receptor-dependent prostate cancer cells

Androgen deprivation therapy (ADT) targeting androgen production and androgen receptor (AR) signaling is the primary antihormonal therapy in the treatment of advanced prostate cancer (PCa). However, no clinically established molecular biomarkers have been identified to predict the effectiveness of ADT before starting ADT. The tumor microenvironment of PCa contains fibroblasts that regulate PCa progression by producing multiple soluble factors. We have previously reported that AR-activating factor-secreted fibroblasts increase the responsiveness of androgen-sensitive, AR-dependent PCa cells to ADT. Thus, we hypothesized that fibroblast-derived soluble factors may affect cancer cell differentiation by regulating cancer-related gene expression in PCa cells and that the biochemical characteristics of fibroblasts may be used to predict the effectiveness of ADT. Here, we investigated the effects of normal fibroblasts (PrSC cells) and three PCa patient-derived fibroblast lines (pcPrF-M5, -M28, and -M31 cells) on the expression of cancer-related genes in androgen-sensitive, AR-dependent human PCa cells (LNCaP cells) and three sublines showing different androgen sensitivities and AR dependencies. The mRNA expression of the tumor suppressor gene NKX3-1 in LNCaP cells and E9 cells (which show low androgen sensitivity and AR dependency) was significantly increased by treatment with conditioned media from PrSC and pcPrF-M5 cells but not from pcPrF-M28 and pcPrF-M31 cells. Notably, no upregulation of NKX3-1 was observed in F10 cells (AR-V7-expressing, AR-independent cells with low androgen sensitivity) and AIDL cells (androgen-insensitive, AR-independent cells). Among 81 common fibroblast-derived exosomal microRNAs that showed 0.5-fold lower expression in pcPrF-M28 and pcPrF-M31 cells than in PrSC and pcPrF-M5 cells, miR-449c-3p and miR-3121-3p were found to target NKX3-1. In only LNCaP cells, the NKX3-1 mRNA expression was significantly increased by transfection of an miR-3121-3p mimic but not that of the miR-449c-3p mimic. Thus, fibroblast-derived exosomal miR-3121-3p may be involved in preventing the oncogenic dedifferentiation of PCa cells by targeting NKX3-1 in androgen-sensitive, AR-dependent PCa cells.

Clinical analysis of EV-Fingerprint to predict grade group 3 and above prostate cancer and avoid prostate biopsy

BACKGROUND

There is an unmet clinical need for minimally invasive diagnostic tests to improve the detection of grade group (GG) ≥3 prostate cancer relative to prostate antigen-specific risk calculators. We determined the accuracy of the blood-based extracellular vesicle (EV) biomarker assay (EV Fingerprint test) at the point of a prostate biopsy decision to predict GG ≥3 from GG ≤2 and avoid unnecessary biopsies.

METHODS

This study analyzed 415 men referred to urology clinics and scheduled for a prostate biopsy, were recruited to the APCaRI 01 prospective cohort study. The EV machine learning analysis platform was used to generate predictive EV models from microflow data. Logistic regression was then used to analyze the combined EV models and patient clinical data and generate the patients' risk score for GG ≥3 prostate cancer.

RESULTS

The EV-Fingerprint test was evaluated using the area under the curve (AUC) in discrimination of GG ≥3 from GG ≤2 and benign disease on initial biopsy. EV-Fingerprint identified GG ≥3 cancer patients with high accuracy (0.81 AUC) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cutoff, 95% of men with GG ≥3 would have been recommended a biopsy while avoiding 144 unnecessary biopsies (35%) and missing four GG ≥3 cancers (5%). Conversely, a 5% cutoff would have avoided 31 unnecessary biopsies (7%), missing no GG ≥3 cancers (0%).

CONCLUSIONS

EV-Fingerprint accurately predicted GG ≥3 prostate cancer and would have significantly reduced unnecessary prostate biopsies.

Clinical Nomogram Using Novel Computed Tomography-Based Radiomics Predicts Survival in Patients With Non-Small-Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy

PURPOSE

Improved survival prediction and risk stratification in non-small-cell lung cancer (NSCLC) would lead to better prognosis counseling, adjuvant therapy selection, and clinical trial design. We propose the persistent homology (PHOM) score, the radiomic quantification of solid tumor topology, as a solution.

MATERIALS AND METHODS

Patients diagnosed with stage I or II NSCLC primarily treated with stereotactic body radiation therapy (SBRT) were selected (N = 554). The PHOM score was calculated for each patient's pretreatment computed tomography scan (October 2008-November 2019). PHOM score, age, sex, stage, Karnofsky Performance Status, Charlson Comorbidity Index, and post-SBRT chemotherapy were predictors in the Cox proportional hazards models for OS and cancer-specific survival. Patients were split into high- and low-PHOM score groups and compared using Kaplan-Meier curves for overall survival (OS) and cumulative incidence curves for cause-specific death. Finally, we generated a validated nomogram to predict OS, which is publicly available at Eashwarsoma.Shinyapps.

RESULTS

PHOM score was a significant predictor for OS (hazard ratio [HR], 1.17; 95% CI, 1.07 to 1.28) and was the only significant predictor for cancer-specific survival (1.31; 95% CI, 1.11 to 1.56) in the multivariable Cox model. The median survival for the high-PHOM group was 29.2 months (95% CI, 23.6 to 34.3), which was significantly worse compared with the low-PHOM group (45.4 months; 95% CI, 40.1 to 51.8; P < .001). The high-PHOM group had a significantly greater chance of cancer-specific death at post-treatment month 65 (0.244; 95% CI, 0.192 to 0.296) compared with the low-PHOM group (0.171; 95% CI, 0.123 to 0.218; P = .029).

CONCLUSION

The PHOM score is associated with cancer-specific survival and predictive of OS. Our developed nomogram can be used to inform clinical prognosis and assist in making post-SBRT treatment considerations.

TRUSformer: improving prostate cancer detection from micro-ultrasound using attention and self-supervision

PURPOSE

A large body of previous machine learning methods for ultrasound-based prostate cancer detection classify small regions of interest (ROIs) of ultrasound signals that lie within a larger needle trace corresponding to a prostate tissue biopsy (called biopsy core). These ROI-scale models suffer from weak labeling as histopathology results available for biopsy cores only approximate the distribution of cancer in the ROIs. ROI-scale models do not take advantage of contextual information that are normally considered by pathologists, i.e., they do not consider information about surrounding tissue and larger-scale trends when identifying cancer. We aim to improve cancer detection by taking a multi-scale, i.e., ROI-scale and biopsy core-scale, approach.

METHODS

Our multi-scale approach combines (i) an "ROI-scale" model trained using self-supervised learning to extract features from small ROIs and (ii) a "core-scale" transformer model that processes a collection of extracted features from multiple ROIs in the needle trace region to predict the tissue type of the corresponding core. Attention maps, as a by-product, allow us to localize cancer at the ROI scale.

RESULTS

We analyze this method using a dataset of micro-ultrasound acquired from 578 patients who underwent prostate biopsy, and compare our model to baseline models and other large-scale studies in the literature. Our model shows consistent and substantial performance improvements compared to ROI-scale-only models. It achieves [Formula: see text] AUROC, a statistically significant improvement over ROI-scale classification. We also compare our method to large studies on prostate cancer detection, using other imaging modalities.

CONCLUSIONS

Taking a multi-scale approach that leverages contextual information improves prostate cancer detection compared to ROI-scale-only models. The proposed model achieves a statistically significant improvement in performance and outperforms other large-scale studies in the literature. Our code is publicly available at www.github.com/med-i-lab/TRUSFormer .

Association between Expression of Connective Tissue Genes and Prostate Cancer Growth and Progression

To find an association between genomic features of connective tissue and pejorative clinical outcomes on radical prostatectomy specimens. We performed a retrospective analysis of patients who underwent radical prostatectomy and underwent a Decipher transcriptomic test for localized prostate cancer in our institution (n = 695). The expression results of selected connective tissue genes were analyzed after multiple t tests, revealing significant differences in the transcriptomic expression (over- or under-expression). We investigated the association between transcript results and clinical features such as extra-capsular extension (ECE), clinically significant cancer, lymph node (LN) invasion and early biochemical recurrence (eBCR), defined as earlier than 3 years after surgery). The Cancer Genome Atlas (TCGA) was used to evaluate the prognostic role of genes on progression-free survival (PFS) and overall survival (OS). Out of 528 patients, we found that 189 had ECE and 27 had LN invasion. The Decipher score was higher in patients with ECE, LN invasion, and eBCR. Our gene selection microarray analysis showed an overexpression in both ECE and LN invasion, and in clinically significant cancer for COL1A1, COL1A2, COL3A1, LUM, VCAN, FN1, AEBP1, ASPN, TIMP1, TIMP3, BGN, and underexpression in FMOD and FLNA. In the TCGA population, overexpression of these genes was correlated with worse PFS. Significant co-occurrence of these genes was observed. When presenting overexpression of our gene selection, the 5-year PFS rate was 53% vs. 68% (p = 0.0315). Transcriptomic overexpression of connective tissue genes correlated to worse clinical features, such as ECE, clinically significant cancer and BCR, identifying the potential prognostic value of the gene signature of the connective tissue in prostate cancer. TCGAp cohort analysis showed a worse PFS in case of overexpression of the connective tissue genes.

ZNF750: A Novel Prognostic Biomarker in Metastatic Prostate Cancer

Prostate cancer is the most frequently diagnosed cancer and the fifth leading cause of cancer death among men in 2020. The clinical decision making for prostate cancer patients is based on the stratification of the patients according to both clinical and pathological parameters such as Gleason score and prostate-specific antigen levels. However, these tools still do not adequately predict patient outcome. The aim of this study was to investigate whether ZNF750 could have a role in better stratifying patients, identifying those with a higher risk of metastasis and with the poorest prognosis. The data reported here revealed that ZNF750 protein levels are reduced in human prostate cancer samples, and this reduction is even higher in metastatic samples. Interestingly, nuclear positivity is significantly reduced in patients with metastatic prostate cancer, regardless of both Gleason score and grade group. More importantly, the bioinformatics analysis indicates that ZNF750 expression is positively correlated with better prognosis. Overall, our findings suggest that nuclear expression of ZNF750 may be a reliable prognostic biomarker for metastatic prostate cancer, which lays the foundation for the development of new biological therapies.

Dysregulation of the PRUNE2/PCA3 genetic axis in human prostate cancer: from experimental discovery to validation in two independent patient cohorts

Background

We have previously shown that the long non-coding (lnc)RNA prostate cancer associated 3 (PCA3; formerly prostate cancer antigen 3) functions as a trans-dominant negative oncogene by targeting the previously unrecognized prostate cancer suppressor gene PRUNE2 (a homolog of the Drosophila prune gene), thereby forming a functional unit within a unique allelic locus in human cells. Here, we investigated the PCA3/PRUNE2 regulatory axis from early (tumorigenic) to late (biochemical recurrence) genetic events during human prostate cancer progression.

Methods

The reciprocal PCA3 and PRUNE2 gene expression relationship in paired prostate cancer and adjacent normal prostate was analyzed in two independent retrospective cohorts of clinically annotated cases post-radical prostatectomy: a single-institutional discovery cohort (n=107) and a multi-institutional validation cohort (n=497). We compared the tumor gene expression of PCA3 and PRUNE2 to their corresponding expression in the normal prostate. We also serially examined clinical/pathological variables including time to disease recurrence.

Results

We consistently observed increased expression of PCA3 and decreased expression of PRUNE2 in prostate cancer compared with the adjacent normal prostate across all tumor grades and stages. However, there was no association between the relative gene expression levels of PCA3 or PRUNE2 and time to disease recurrence, independent of tumor grades and stages.

Conclusions

We concluded that upregulation of the lncRNA PCA3 and targeted downregulation of the protein-coding PRUNE2 gene in prostate cancer could be early (rather than late) molecular events in the progression of human prostate tumorigenesis but are not associated with biochemical recurrence. Further studies of PCA3/PRUNE2 dysregulation are warranted.

Funding

We received support from the Human Tissue Repository and Tissue Analysis Shared Resource from the Department of Pathology of the University of New Mexico School of Medicine and a pilot award from the University of New Mexico Comprehensive Cancer Center. RP and WA were supported by awards from the Levy-Longenbaugh Donor-Advised Fund and the Prostate Cancer Foundation. EDN reports research fellowship support from the Brazilian National Council for Scientific and Technological Development (CNPq), Brazil, and the Associação Beneficente Alzira Denise Hertzog Silva (ABADHS), Brazil. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of New Mexico Comprehensive Cancer Center (CA118100) and the Rutgers Cancer Institute of New Jersey (CA072720).

Clinical and molecular significance of the RNA m6A methyltransferase complex in prostate cancer

N⁶-methyladenosine (m⁶A) is the most abundant internal mRNA modification and is dynamically regulated through distinct protein complexes that methylate, demethylate, and/or interpret the m⁶A modification. These proteins, and the m⁶A modification, are involved in the regulation of gene expression, RNA stability, splicing and translation. Given its role in these crucial processes, m⁶A has been implicated in many diseases, including in cancer development and progression. Prostate cancer (PCa) is the most commonly diagnosed non-cutaneous cancer in men and recent studies support a role for m⁶A in PCa. Despite this, the literature currently lacks an integrated analysis of the expression of key components of the m⁶A RNA methyltransferase complex, both in PCa patients and in well-established cell line models. For this reason, this study used immunohistochemistry and functional studies to investigate the mechanistic and clinical significance of the METTL3, METTL14, WTAP and CBLL1 components of the m⁶A methyltransferase complex in PCa specimens and cell lines. Expression of METTL3 and CBLL1, but not METTL14 and WTAP, was associated with poorer PCa patient outcomes. Expression of METTL3, METTL14, WTAP and CBLL1 was higher in PCa cells compared with non-malignant prostate cells, with the highest expression seen in castrate-sensitive, androgen-responsive PCa cells. Moreover, in PCa cell lines, expression of METTL3 and WTAP was found to be androgen-regulated. To investigate the mechanistic role(s) of the m⁶A methyltransferase complex in PCa cells, short hairpin RNA (shRNA)-mediated knockdown coupled with next generation sequencing was used to determine the transcriptome-wide roles of METTL3, the catalytic subunit of the m⁶A methyltransferase complex. Functional depletion of METTL3 resulted in upregulation of the androgen receptor (AR), together with 134 AR-regulated genes. METTL3 knockdown also resulted in altered splicing, and enrichment of cell cycle, DNA repair and metabolic pathways. Collectively, this study identified the functional and clinical significance of four essential m⁶A complex components in PCa patient specimens and cell lines for the first time. Further studies are now warranted to determine the potential therapeutic relevance of METTL3 inhibitors in development to treat leukaemia to benefit patients with PCa.

Expression of Claudin-4 and D2-40 and their significance in prostatic adenocarcinoma

BACKGROUND

Claudins are a clan of proteins that are the most important component of tight junctions. The claudin-4 expression has been linked to tumour cell invasion and progression in a variety of primary malignancies. Evaluation of lymphovascular density (LVD) correlates with tumour aggressiveness and may correlate with prognosis. D2-40 is a highly specific marker of lymphatic vessels.

AIMS

To evaluate the claudin-4 expression in relation to LVD by D2-40 expression and with clinicopathological parameters in prostatic adenocarcinoma.

SETTINGS AND DESIGN

Prospective study.

MATERIALS AND METHODS

39 cases of prostatic adenocarcinoma were taken, the D2-40 and claudin-4 immunohistochemical stains were performed and correlation was done with clinicopathological parameters.

STATISTICAL ANALYSIS USED

Statistical analyses such as mean, median, standard deviation, Mann-Whitney U test, Fischer exact test, Spearman's rank-order correlation coefficient, Chi-square test and T-test were used.

RESULTS

The claudin-4 expression was seen higher in cases with higher Gleason score but it was statistically non-significant (P = 0.778). The claudin-4 expression did not correlate with any clinicopathological parameters. LVD in the peritumoral area was significantly higher as compared to the intratumoral area (P = 0.005). Intratumoral LVD and perineural invasion were found to be statistically significant (P = 0.048).

CONCLUSION

The claudin-4 expression may correlate with adverse prognostic parameters. Higher lymphatic vessels can be responsible for the higher metastatic potential of prostatic adenocarcinomas.

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

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

Forecasting of overall and aggressive prostate cancer incident counts at the small area level

OBJECTIVES

This study aims to forecast overall and aggressive prostate cancer counts at the local government area (LGA) level over 10 years (2019-2028) in Victoria, Australia, using Victorian Cancer Registry (2001-2018) data.

METHODS

We used the Age-Period-Cohort approach to estimate the annual age-specific incidence and used Bayesian spatiotemporal models that account for non-linear temporal trends and area-level risk factors. We evaluated the models' performance by withholding and comparing forecasts with the 2014-2018 data.

RESULTS

There were 80,449 prostate cancer cases between 2001 and 2018, with an overall increasing trend. Compared to 2001, prostate cancer incidence increased by 69%, from 3049 to 5167 cases in 2018. Prostate cancer counts are expected to reach 7631 cases in 2028, a further 48% increase. Unexplained area-level spatial variation was substantially reduced after adjusting for the area-level elderly population. Aggressive prostate cancer cases increased by 107% between 2001 and 2018 and are expected to rise by 123% increase in 2028. The proportion of aggressive prostate cancer cases will increase to 31% in 2028 from 20% in 2018. By 2028, overall and aggressive prostate cancer cases are projected to be increasing in 66% and 61% of LGAs.

CONCLUSION

Prostate cancer cases are projected to rise at the state level and most LGAs in the next 10 years, with much steeper increases in aggressive cases. Population growth and an ageing population have primarily contributed to this rise besides prostate-specific antigen testing. These prediction estimates help inform prostate cancer burden and facilitate efficient healthcare delivery.

Discovery and Validation of Clinically Relevant Long Non-Coding RNAs in Colorectal Cancer

Simple Summary

Recent efforts in biomedical research have focused on the identification of molecular biomarkers to improve the diagnosis, prognosis and eventually treatment of the most common human diseases worldwide, including cancer. In this context, a large number of studies point to a pivotal role of long non-coding RNAs (lncRNAs) in the pathophysiology of carcinogenesis, suggesting diagnostic or therapeutic potential. However, for most of them, supporting evidence is scarce and often based on a single large-scale analysis. Here, focusing on colorectal cancer (CRC), we present an overview of the main approaches for discovering and validating lncRNA candidate molecules, and provide a curated list of the most promising lncRNAs associated with this malignancy.

Abstract

Colorectal cancer (CRC) is the third most prevalent cancer worldwide, with nearly two million newly diagnosed cases each year. The survival of patients with CRC greatly depends on the cancer stage at the time of diagnosis, with worse prognosis for more advanced cases. Consequently, considerable effort has been directed towards improving population screening programs for early diagnosis and identifying prognostic markers that can better inform treatment strategies. In recent years, long non-coding RNAs (lncRNAs) have been recognized as promising molecules, with diagnostic and prognostic potential in many cancers, including CRC. Although large-scale genome and transcriptome sequencing surveys have identified many lncRNAs that are altered in CRC, most of their roles in disease onset and progression remain poorly understood. Here, we critically review the variety of detection methods and types of supporting evidence for the involvement of lncRNAs in CRC. In addition, we provide a reference catalog that features the most clinically relevant lncRNAs in CRC. These lncRNAs were selected based on recent studies sorted by stringent criteria for both supporting experimental evidence and reproducibility.

Prostate cancer: understanding patients' treatment options

Prostate cancer is the most common cancer among men in the UK. It is a disease with no specific preventable risk factors, no specific signs and symptoms, and a significant health burden. This article explains the various treatment options available for patients with prostate cancer, with the aim of assisting nurses in supporting person-centred decision-making. It also discusses the risk factors, signs and symptoms, diagnosis, staging, grading and risk stratification of prostate cancer.

Secreted miR-153 Controls Proliferation and Invasion of Higher Gleason Score Prostate Cancer

Prostate cancer (PC) is a male common neoplasm and is the second leading cause of cancer death in American men. PC is traditionally diagnosed by the evaluation of prostate secreted antigen (PSA) in the blood. Due to the high levels of false positives, digital rectal examination and transrectal ultrasound guided biopsy are necessary in uncertain cases with elevated PSA levels. Nevertheless, the high mortality rate suggests that new PC biomarkers are urgently needed to help clinical diagnosis. In a previous study, we have identified a network of genes, altered in high Gleason Score (GS) PC (GS ≥ 7), being regulated by miR-153. Until now, no publication has explained the mechanism of action of miR-153 in PC. By in vitro studies, we found that the overexpression of miR-153 in high GS cell lines is required to control cell proliferation, migration and invasion rates, targeting Kruppel-like factor 5 (KLF5). Moreover, miR-153 could be secreted by exosomes and microvesicles in the microenvironment and, once entered into the surrounding tissue, could influence cellular growth. Being upregulated in high GS human PC, miR-153 could be proposed as a circulating biomarker for PC diagnosis.

A comparison of clinicopathologic features of prostate cancer between Nigerian and South African black men

Background

Globally, prostate cancer (PCa) is the commonest non-cutaneous male malignancy. It is more aggressive among black men with little known reasons as to the cause and continued trend among black men. This disproportionate pattern of PCa especially among black men of African ancestry resident in Africa calls for a closer look. Nigeria and South Africa, combined, have the highest cumulative risk incidence of PCa in Africa. The present study investigated the clinicopathologic behaviour of PCa among Nigerian and South African black men and the relationship between the disease and socio-demographic characteristics alongside medical co-morbidities.

Methods

A retrospective cross-sectional study was undertaken in which de-identified records of 234 black men with pathologically confirmed PCa between 2007 and 2017 from two tertiary hospitals, in Nigeria (National Hospital, Abuja) and South Africa (Tygerberg Hospital, Cape Town), were reviewed.

Results

Median age at presentation from both countries was 66 years (interquartile range, IQR 61–73 years) while the median PSA at presentation was 46 ng/ml (IQR 16–336.5 ng/ml). Half of the men (117/234) presented with locally advanced disease while metastatic disease was observed in 65.9% (27/41) of Nigerian men and 34.1% (14/41) of South African men. Thirty-three per cent of the men presented with organ-confined disease. Overall, Nigerian men presented with less organ-confined disease and significantly higher stage of disease (p < 0.001). Risk stratification using PSA, Gleason scores and T-staging showed that 84.2% (n = 197) of all the men presented with high-risk PCa disease. There was a statistically significant difference between Nigerian and South African black men (p = 0.003) in terms of disease risk at presentation. Logistic regression analysis showed that age (Adjusted OR 1.053 (95% CI 1.003–1.106), p = 0.003) and country of residence (Adjusted OR 4.281 (95% CI 1.690–10.844), p = 0.002) had a statistically significant relationship with high risk of PCa while disease co-morbidities (like diabetes and hypertension) and rural/urban location in both countries did not.

Conclusions

Disparities exist between PCa presentation and clinicopathologic behaviour among Nigerian and South African black men. Nigerian men showed higher disease risk at presentation. Environmental-genetic interactions need further exploration in the aetio-pathogenesis of PCa in black men of African ancestry.

Exploring the Role of Testosterone Replacement Therapy in Benign Prostatic Hyperplasia and Prostate Cancer: A Review of Safety

Increased risk of prostate diseases triggered by testosterone replacement therapy (TRT) remains a worldwide concern. That said, we reviewed the safety of TRT in the spheres of benign prostatic hyperplasia (BPH) and prostate cancer (PCa), exploring clinical findings in this regard. Compelling evidence based on meta-analyses of randomized and observational studies indicates safety for TRT in patients suffering from prostate disorders such as BPH and PCa, at the same time improving lower tract urinary symptoms. Thus, the harmful relationship geared toward androgens and BPH seems to be overestimated as TRT has sufficient safety and, if properly prescribed, may counteract several metabolic problems. Even after PCa treatment, the benefits of TRT could outweigh the risk of recurrence, but further long-term randomized clinical trials are needed to elucidate unresolved questions.

Health Disparities of Sexual Minority Patients Following Prostate Cancer Treatment: Results From the Restore-2 Study

PURPOSE

The NIH has identified sexual and gender minority persons as a health disparity population but little is known about cancer outcomes in these populations. The purpose of this study was to identify disparities in sexual minority prostate cancer patient-reported outcomes, to examine within group differences, and to test for alternative explanations for identified differences.

MATERIALS AND METHODS

In 2019, we recruited 401 gay and bisexual prostate cancer patients into the Restore-2 study, a randomized controlled trial of rehabilitation program tailored for sexual minority men.

RESULTS

Compared to the normative (heterosexual) EPIC sample, participants had significantly worse urinary, bowel and hormonal function, better sexual function, and no difference on bother scores. They also had worse depression and overall mental health, and worse physical, social/family, functional, prostate specific and overall well-being quality of life outcomes. Across measures, no differences by age, gay versus bisexual orientation, race/ethnicity, and relationship status were observed. Those who had hormonal treatment had worse sexual and hormonal function than those who had radiation or surgery only. Those with a longer time since treatment had better urinary function. Differences remained when participants were matched to normative samples on cancer stage and time since treatment.

CONCLUSIONS

This, the largest study of sexual minority prostate cancer patients to date, confirms health disparities in prostate cancer quality of life outcomes. Findings appear reliable and robust. To improve the clinical care of prostate cancer, it will be important to address the health disparities experienced by sexual minority prostate cancer patients.

Impact of prostate biopsy secondary pathology review on radiotherapy management

BACKGROUND

The Gleason scoring system is the most widely used method to assess prostate adenocarcinoma pathology however interobserver variability is significant. Gleason score, PSA level, and clinical stage comprise the NCCN risk stratification that guides treatment decision making. Given the importance of an accurate Gleason score and wide interobserver variability, referral centers routinely review outside pathology at the time of consultation. We sought to address the impact a secondary pathology review had on radiation therapy treatment recommendations in men with prostate cancer at our institution.

METHODS

We retrospectively collected patient data on 342 patients seen at our institution from January 2012 to December 2018. Clinicopathologic data were used to subdivide patients into risk groups and available treatment options per NCCN criteria. Cases reviewed by our genitourinary pathologist (GUP) were compared with reports from outside pathologists. Inter-rater reliability between pathologists was assessed with weighted Cohen's kappa statistic and agreement of treatment options was determined by McNemar's exact tests.

RESULTS

GUP scored more cores positive in 16.47% of cases on secondary review. Primary Gleason score was changed in 12.28% of patients and secondary score in 26.02% of cases. Total Gleason score was different in 29.24% of cases, 19.01% were downgraded and 10.23% upgraded. The weighted kappa statistic was 0.759 (95% confidence interval [CI]: 0.711, 0.807). 18.77% of patients were assigned to a different NCCN risk group following secondary review. The weighted kappa statistic comparing NCCN risk stratification was 0.802 (95% CI: 0.754, 0.850). Secondary review influenced radiation therapy recommendations pertaining to brachytherapy boost and androgen deprivation therapy in men with high risk disease (χ²  = 5.33, p = 0.0386; χ²  = 8.05, p = 0.0072, respectively). Kappa statistic was found to be highest when GUP assessed high-risk disease versus all other categories (κ = 0.823, 95% CI: 0.750, 0.895).

CONCLUSIONS

We found nearly one in five men (18.7%) was assigned a different NCCN risk group and thus offered potentially different treatment options after a secondary pathology review at our institution. Given the inherent nature of prostate cancer and lung disease-specific survival associated with modern therapies, our study demonstrates the importance of a secondary pathology review and its potential impact on radiation therapy recommendations.

Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment

Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.

Assessment of factors associated with PSA level in prostate cancer cases and controls from three geographical regions

It is being debated whether prostate-specific antigen (PSA)-based screening effectively reduces prostate cancer mortality. Some of the uncertainty could be related to deficiencies in the age-based PSA cut-off thresholds used in screening. Current study considered 2779 men with prostate cancer and 1606 men without a cancer diagnosis, recruited for various studies in New Zealand, US, and Taiwan. Association of PSA with demographic, lifestyle, clinical characteristics (for cases), and the aldo–keto reductase 1C3 (AKR1C3) rs12529 genetic polymorphisms were analysed using multiple linear regression and univariate modelling. Pooled multivariable analysis of cases showed that PSA was significantly associated with demographic, lifestyle, and clinical data with an interaction between ethnicity and age further modifying the association. Pooled multivariable analysis of controls data also showed that demographic and lifestyle are significantly associated with PSA level. Independent case and control analyses indicated that factors associated with PSA were specific for each cohort. Univariate analyses showed a significant age and PSA correlation among all cases and controls except for the US-European cases while genetic stratification in cases showed variability of correlation. Data suggests that unique PSA cut-off thresholds factorized with demographics, lifestyle and genetics may be more appropriate for prostate cancer screening.

Histopathological Study of the Prostate Cancer Growth Patterns in Relation with the Grading Systems

Prostate adenocarcinomas are common lesions with a high incidence and variable prognosis, which can be assessed using tumor grading systems. In this study, we analyzed 329 prostate adenocarcinomas in relation to tumor variants, growth patterns, classical and updated grading systems. The study indicated statistical associations of atrophic, pseudohyperplastic and microcystic variants with low grading scores, the associations of glomeruloid, cribriform with or without necrosis and signet ring-like cell variants with high grading scores, and also of single growth patterns with intermediate scores, which supports the accordance and usefulness of existing grading systems for the identification of aggressive prostate tumor lesions.

International Society of Urological Pathology (ISUP)-Grade Grouping in Prostatic Adenocarcinoma and its Prognostic Implications

In this study, we evaluated the association of ISUP/WHO-grade groups with various pathological prognostic parameters and cancer-specific survival in patients with prostatic adenocarcinoma. We found 27 (15.7%) cases of grade group 1, 22 (12.8%) grade group 2, 30 (17.4%) grade group 3, 40 (23.3%) grade group 4 and 53 (30.8%) grade group 5 prostatic adenocarcinoma. We found that high-grade tumors (grade 3-5) had a higher frequency of perineural invasion and higher tumor volumes (>50%). Moreover, a significant association of tumor grade was noted with cancer-specific survival of patients, signifying prognostic significance of grade grouping in prostatic adenocarcinoma.

Prognostic value of miR-21 for prostate cancer: a systematic review and meta-analysis

Elevated levels of miR-21 expression are associated with many cancers, suggesting it may be a promising clinical biomarker. In prostate cancer (PCa), however, there is still no consensus about the usefulness of miR-21 as an indicator of disease progression. This systematic review and meta-analysis was conducted to investigate the value of miR-21 expression as a prognostic measurement in PCa patients. Medline (Ovid), EMBASE, Web of Science, Scopus and Cochrane Library databases were systematically searched for relevant publications between 2010 to 2021. Studies exploring the relationship between miR-21 expression, PCa prognosis and clinicopathological factors were selected for review. Those reporting hazard ratio (HR) and 95% confidence intervals (CIs) were subject to meta-analyses. Fixed-effect models were employed to calculated pooled HRs and 95% CIs. Risk of bias in each study was assessed using QUIPS tool. Certainty of evidence in each meta-analysis was assessed using GRADE guidelines. A total of 64 studies were included in the systematic review. Of these, 11 were eligible for inclusion in meta-analysis. Meta-analyses revealed that high miR-21 expression was associated with poor prognosis: HR = 1.58 (95% CI = 1.19–2.09) for biochemical recurrence, MODERATE certainty; HR = 1.46 (95% CI = 1.06–2.01) for death, VERY LOW certainty; and HR = 1.26 (95% CI = 0.70–2.27) for disease progression, VERY LOW certainty. Qualitative summary revealed elevated miR-21 expression was significantly positively associated with PCa stage, Gleason score and risk groups. This systematic review and meta-analysis suggests that elevated levels of miR-21 are associated with poor prognosis in PCa patients. miR-21 expression may therefore be a useful prognostic biomarker in this disease.

Insights of RKIP-Derived Suppression of Prostate Cancer

Simple Summary

Despite an intensive research effort in the past few decades, prostate cancer (PC) remains a top cause of cancer death in men, particularly in the developed world. The major cause of fatality is the progression of local prostate cancer to metastasis disease. Treatment of patients with metastatic prostate cancer (mPC) is generally ineffective. Based on the discovery of mPC relying on androgen for growth, many patients with mPC show an initial response to the standard of care: androgen deprivation therapy (ADT). However, lethal castration resistant prostate cancers (CRPCs) commonly develop. It is widely accepted that intervention of metastatic progression of PC is a critical point of intervention to reduce PC death. Accumulative evidence reveals a role of RKIP in suppression of PC progression towards mPC. We will review current evidence and discuss the potential utilization of RKIP in preventing mPC progression.

Abstract

Prostate cancer (PC) is a major cause of cancer death in men. The disease has a great disparity in prognosis. Although low grade PCs with Gleason scores ≤ 6 are indolent, high-risk PCs are likely to relapse and metastasize. The standard of care for metastatic PC (mPC) remains androgen deprivation therapy (ADT). Resistance commonly occurs in the form of castration resistant PC (CRPC). Despite decades of research efforts, CRPC remains lethal. Understanding of mechanisms underpinning metastatic progression represents the overarching challenge in PC research. This progression is regulated by complex mechanisms, including those regulating PC cell proliferation, epithelial–mesenchymal transition (EMT), and androgen receptor (AR) signaling. Among this PC metastatic network lies an intriguing suppressor of PC metastasis: the Raf kinase inhibitory protein (RKIP). Clinically, the RKIP protein is downregulated in PC, and showed further reduction in mPC. In xenograft mouse models for PC, RKIP inhibits metastasis. In vitro, RKIP reduces PC cell invasion and sensitizes PC cells to therapeutic treatments. Mechanistically, RKIP suppresses Raf-MEK-ERK activation and EMT, and modulates extracellular matrix. In return, Snail, NFκB, and the polycomb protein EZH2 contribute to inhibition of RKIP expression. In this review, we will thoroughly analyze RKIP’s tumor suppression actions in PC.

Cribriform glands are associated with worse outcome than other pattern 4 subtypes: A study of prognostic and clinicopathological characteristics of prostate adenocarcinoma with an emphasis on Grade Groups

AIM

Although prostate adenocarcinoma is the most common cancer in men, survival is quite high and with the help of histopathological examination using the updated classification, patient management strategies are developing. We aimed to evaluate the correlation between the histopathological features and biochemical recurrence (BCR) in patients who underwent radical prostatectomy (RP) using the new classification.

METHODS

A total of 285 prostate adenocarcinoma cases that underwent RP between January 2009 and December 2017 and followed up for at least 3 months were included in the study. The cases were re-evaluated according to WHO-ISUP 2016 classification and the findings were recorded.

RESULTS

The mean age was 63,4 years. Gleason scores of the cases were as follows: 3+3 144 cases (50.5%), 3+4 81 cases (28.4%), 4+3 28 cases (9.8%), 4+4 7 cases (2.5%) , 3+5 6 cases (2.1%), 5+3 2 cases (0.7%), 4+5 17 cases (6%). There were 198 (69,5%) pT2, 54 (18,9%) pT3a and 33 (11,6%) pT3b cases. The mean follow-up time was 44,1 months and BCR was detected in 97 cases (34%). The relationship between the Group Grades and BCR was statistically significant. BCR rate increased as the tumour volume and the percentage of pattern 4 increased (P < .001).There was a significant correlation between preoperative PSA value, extraprostatic extension, seminal vesicle invasion, surgical margin positivity, tumour volume, pattern 4 percentage, presence of cribriform glands and BCR and recurrence-free survival in both univariate and multivariate analysis and recurrence-free survival was also affected by these parameters. Among the morphological subtypes of Pattern 4, recurrence-free survival decreased as the incidence of cribriform glands increased (P < .001).

CONCLUSION

Histopathological evaluation is important in predicting BCR in prostate adenocarcinoma, the Group Grade system seems to be helpful in this regard. More studies are needed to prove the relatively worse prognostic effect of cribriform glands.

Persistent homology of tumor CT scans is associated with survival in lung cancer

PURPOSE

Radiomics, the objective study of nonvisual features in clinical imaging, has been useful in informing decisions in clinical oncology. However, radiomics currently lacks the ability to characterize the overall topological structure of the data. This niche can be filled by persistent homology, a form of topological data analysis that analyzes high-level structure. We hypothesized that persistent homology features quantified using cubical complexes could be extracted from lung tumor scans and related to survival.

METHODS

We obtained segmented computed tomography (CT) lung scans (n = 565) from the NSCLC-Radiomics and NSCLC-Radiogenomics datasets in The Cancer Imaging Archive. These scans are three-dimensional images whose pixel intensity corresponds to a number of Hounsfield units. Cubical complexes are a topological image analysis method that effectively analyzes the number of topological features in an image as the image is thresholded at different intensities. We calculated a novel output called a feature curve by plotting the number of zero-dimensional (0D) topological features counted from the cubical complex filtration against each Hounsfield value. This curve's first moment of distribution was utilized as a summary statistic to show association with survival in a Cox proportional hazards model. We hypothesized that persistent homology features quantified using cubical complexes could be extracted from lung tumor scans and related to survival.

RESULTS

After controlling for tumor image size, age, and stage, the first moment of the 0D topological feature curve was associated with poorer survival (HR = 1.118; 95% CI = 1.026-1.218; p = 0.01). The patients in our study with the lowest first moment scores had significantly better survival (1238 days; 95% CI = 936-1599) compared to the patients with the highest first moment scores (429 days; 95% CI = 326-601; p = 0.0015).

CONCLUSIONS

We have shown that persistent homology can generate useful clinical correlates from tumor CT scans. Our 0D topological feature curve statistic predicts survival in lung cancer patients. This novel statistic may be used in tandem with standard radiomics variables to better inform clinical oncology decisions.

[Localized prostate cancer]

Prostate cancer is the most prevalent noncutaneous cancer in men. The Gleason grading is considered to be the strongest prognostic parameter regarding progression-free survival and overall survival. The original grading system has been modified during the last decade resulting in a more precise prognostic tool. The pretreatment Gleason score guides clinical management and is a key component in S3 guidelines for prostate cancer. In addition to Gleason score several other histologic findings in prostate needle biopsy influence patient management. In this second part of our CME series about prostate cancer, we will discuss the diagnosis of prostate cancer and current guidelines for reporting prostate cancer. In addition, we will highlight prostate lesions of urothelial origin and neuroendocrine prostate cancer as well as prognostic biomarkers.

Combination MRI-targeted and systematic prostate biopsy may overestimate gleason grade on final surgical pathology and impact risk stratification

PURPOSE

Gleason grade (GG) on prostate biopsy is important for risk stratification and clinical decision making. Multiparametric MRI (mpMRI) improved detection of clinically significant disease and some studies suggest that MRI-fusion biopsy combined with systematic biopsy results in fewer upgrades on final surgical pathology. However, the downgrade rate is unclear and there is controversy in the literature. The objectives of this study are to assess the concordance of combination biopsy with final surgical pathology, and furthermore, to specifically determine downgrade rates.

MATERIALS AND METHODS

In our institutional mpMRI-ultrasound fusion biopsy database, 173 underwent targeted and systematic biopsy followed by radical prostatectomy (RP). GG on targeted, systematic and combination (targeted and systematic) biopsy were compared with GG on RP. Concordance rates between biopsy types were compared with the McNemar test. Proportion of GG upgrade or downgrade at the time of RP was also evaluated.

RESULTS

Surgical pathology was concordant with 44.5% of systematic biopsies, 46.8% of targeted biopsies, and 56.7% of combination biopsies. Combination biopsy significantly overestimated the final GG on RP compared to systematic biopsy (16.8% vs. 8.7% RR 1.93, 95% CI 1.36-2.75, P < 0.001). Downgrade rate from unfavorable to favorable intermediate-risk disease was 46.2%, and from high-risk to intermediate-risk disease was 45.1%.

CONCLUSIONS

Combination (targeted and systematic) biopsy is associated with the highest concordance rate between biopsy and RP pathology when compared with systematic or targeted biopsy alone. However, targeting MRI lesions and therefore the higher risk components, may at times overestimate the final surgical pathology which can result in overtreatment of what may truly be less aggressive disease.

Comparison of Sensitivity and Specificity of Biparametric versus Multiparametric Prostate MRI in the Detection of Prostate Cancer in 431 Men with Elevated Prostate-Specific Antigen Levels

(1) Background: the study of dynamic contrast enhancement (DCE) has a limited role in the detection of prostate cancer (PCa), and there is a growing interest in performing unenhanced biparametric prostate-MRI (bpMRI) instead of the conventional multiparametric-MRI (mpMRI). In this study, we aimed to retrospectively compare the performance of the mpMRI, which includes DCE study, and the unenhanced bpMRI, composed of only T2-weighted imaging and diffusion-weighted imaging (DWI), in PCa detection in men with elevated prostate-specific-antigen (PSA) levels. (2) Methods: a 1.5 T MRI, with an endorectal-coil, was performed on 431 men (aged 61.5 ± 8.3 years) with a PSA ≥4.0 ng/mL. The bpMRI and mpMRI tests were independently assessed in separate sessions by two readers with 5 (R1) and 3 (R2) years of experience. The histopathology or ≥2 years follow-up served as a reference standard. The sensitivity and specificity were calculated with their 95% CI, and McNemar’s and Cohen’s κ statistics were used. (3) Results: in 195/431 (45%) of histopathologically proven PCa cases, 62/195 (32%) were high-grade PCa (GS ≥ 7b) and 133/195 (68%) were low-grade PCa (GS ≤ 7a). The PCa could be excluded by histopathology in 58/431 (14%) and by follow-up in 178/431 (41%) of patients. For bpMRI, the sensitivity was 164/195 (84%, 95% CI: 79–89%) for R1 and 156/195 (80%, 95% CI: 74–86%) for R2; while specificity was 182/236 (77%, 95% CI: 72–82%) for R1 and 175/236 (74%, 95% CI: 68–80%) for R2. For mpMRI, sensitivity was 168/195 (86%, 95% CI: 81–91%) for R1 and 160/195 (82%, 95% CI: 77–87%) for R2; while specificity was 184/236 (78%, 95% CI: 73–83%) for R1 and 177/236 (75%, 95% CI: 69–81%) for R2. Interobserver agreement was substantial for both bpMRI (κ = 0.802) and mpMRI (κ = 0.787). (4) Conclusions: the diagnostic performance of bpMRI and mpMRI were similar, and no high-grade PCa was missed with bpMRI.

Revisiting extraprostatic extension based on invasion depth and number for new algorithm for substaging of pT3a prostate cancer

Extraprostatic extension (EPE) is a factor in determining pT3a stage in prostate cancer. However, the only distinction in EPE is whether it is focal or non-focal, causing diagnostic and prognostic ambiguity. We substaged pT3a malignancies using classification of EPE to improve personalized prognostication. We evaluated 465 radical prostatectomy specimens with a digital image analyzer by measuring the number, radial distance and two-dimensional square area of the EPE. The most significant cut-off value was proposed as an algorithm for the pT3a substaging system to predict biochemical recurrence (BCR). A combination of the radial distance and the number of EPEs predicted BCR the most effectively. The optimal cut-off criteria were 0.75 mm and 2 mm in radial distance and multifocal EPE (hazard ratio: 2.526, C-index 0.656). The pT3a was subdivided into pT3a1, < 0.75 mm and any number of EPEs; pT3a2, 0.75–2 mm and one EPE; and pT3a3, > 2 mm and any number of EPEs or 0.75–2 mm and ≥ 2 EPEs. This combined tier was highly significant in the prediction of BCR-free survival. The combination of radial distance and number of EPEs could be used to subdivide pT3a prostate cancer and may aid in the prediction of BCR.