Diagnostic challenges of clonal heterogeneity in prostate cancer

Molecular Pathology of Prostate Cancer

Molecular profiling studies have shed new light on the complex biology of prostate cancer. Genomic studies have highlighted that structural rearrangements are among the most common recurrent alterations. In addition, both germline and somatic mutations in DNA repair genes are enriched in patients with advanced disease. Primary prostate cancer has long been known to be multifocal, but recent studies demonstrate that a large fraction of prostate cancer shows evidence of multiclonality, suggesting that genetically distinct, independently arising tumor clones coexist. Metastatic prostate cancer shows a high level of morphologic and molecular diversity, which is associated with resistance to systemic therapies. The resulting high level of intratumoral heterogeneity has important implications for diagnosis and poses major challenges for the implementation of molecular studies. Here we provide a concise review of the molecular pathology of prostate cancer, highlight clinically relevant alterations, and discuss opportunities for molecular testing.

Direct three-dimensional segmentation of prostate glands with nnU-Net

Significance

In recent years, we and others have developed non-destructive methods to obtain three-dimensional (3D) pathology datasets of clinical biopsies and surgical specimens. For prostate cancer risk stratification (prognostication), standard-of-care Gleason grading is based on examining the morphology of prostate glands in thin 2D sections. This motivates us to perform 3D segmentation of prostate glands in our 3D pathology datasets for the purposes of computational analysis of 3D glandular features that could offer improved prognostic performance.

Aim

To facilitate prostate cancer risk assessment, we developed a computationally efficient and accurate deep learning model for 3D gland segmentation based on open-top light-sheet microscopy datasets of human prostate biopsies stained with a fluorescent analog of hematoxylin and eosin (H&E).

Approach

For 3D gland segmentation based on our H&E-analog 3D pathology datasets, we previously developed a hybrid deep learning and computer vision-based pipeline, called image translation-assisted segmentation in 3D (ITAS3D), which required a complex two-stage procedure and tedious manual optimization of parameters. To simplify this procedure, we use the 3D gland-segmentation masks previously generated by ITAS3D as training datasets for a direct end-to-end deep learning-based segmentation model, nnU-Net. The inputs to this model are 3D pathology datasets of prostate biopsies rapidly stained with an inexpensive fluorescent analog of H&E and the outputs are 3D semantic segmentation masks of the gland epithelium, gland lumen, and surrounding stromal compartments within the tissue.

Results

nnU-Net demonstrates remarkable accuracy in 3D gland segmentations even with limited training data. Moreover, compared with the previous ITAS3D pipeline, nnU-Net operation is simpler and faster, and it can maintain good accuracy even with lower-resolution inputs.

Conclusions

Our trained DL-based 3D segmentation model will facilitate future studies to demonstrate the value of computational 3D pathology for guiding critical treatment decisions for patients with prostate cancer.

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

As medical science and technology progress towards the era of "big data", a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC's diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy

Simple Summary

Most malignant tumours are highly heterogeneous at molecular and phenotypic levels. Tumour variability poses challenges for the management of patients, as it arises between patients and even evolves in space and time within a single patient. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of tumour diversity in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate tumour heterogeneity.

Abstract

Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.

Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning-Assisted Gland Analysis

Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual inspection of a limited number of two-dimensional (2D) histology sections is often unreliable, which contributes to the under- and overtreatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for nondestructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analogue of standard hematoxylin and eosin (H&E) staining. This analysis is based on interpretable glandular features and is facilitated by the development of image translation-assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep learning-based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring immunolabeling. As a preliminary demonstration of the translational value of a computational 3D versus a computational 2D pathology approach, we imaged 300 ex vivo biopsies extracted from 50 archived radical prostatectomy specimens, of which, 118 biopsies contained cancer. The 3D glandular features in cancer biopsies were superior to corresponding 2D features for risk stratification of patients with low- to intermediate-risk prostate cancer based on their clinical biochemical recurrence outcomes. The results of this study support the use of computational 3D pathology for guiding the clinical management of prostate cancer. SIGNIFICANCE: An end-to-end pipeline for deep learning-assisted computational 3D histology analysis of whole prostate biopsies shows that nondestructive 3D pathology has the potential to enable superior prognostic stratification of patients with prostate cancer.

Cancer evolution: Darwin and beyond

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling

Metastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases.

The inter- and intra-tumor heterogeneity of metastatic prostate cancer (mPC) is underexplored. Here the authors use Digital Spatial Profiling to study gene and protein expression heterogeneity in 27 mPC patients, finding variation in associated pathways and potential immunotherapy targets.

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

Genomic and phenotypic heterogeneity in prostate cancer

From a clinical, morphological and molecular perspective, prostate cancer is a heterogeneous disease. Primary prostate cancers are often multifocal, having topographically and morphologically distinct tumour foci. Sequencing studies have revealed that individual tumour foci can arise as clonally distinct lesions with no shared driver gene alterations. This finding demonstrates that multiple genomically and phenotypically distinct primary prostate cancers can be present in an individual patient. Lethal metastatic prostate cancer seems to arise from a single clone in the primary tumour but can exhibit subclonal heterogeneity at the genomic, epigenetic and phenotypic levels. Collectively, this complex heterogeneous constellation of molecular alterations poses obstacles for the diagnosis and treatment of prostate cancer. However, advances in our understanding of intra-tumoural heterogeneity and the development of novel technologies will allow us to navigate these challenges, refine approaches for translational research and ultimately improve patient care.

Evaluation of Apparent Diffusion Coefficient as a Predictor of Grade Reclassification in Men on Active Surveillance for Prostate Cancer

OBJECTIVE

To evaluate the association between apparent diffusion coefficient (ADC) on initial multiparametric MRI (mpMRI) and biopsy grade reclassification (GR) to grade group (GG) ≥2 prostate cancer (CaP) in men on active surveillance (AS) with GG 1 CaP.

METHODS

We retrospectively identified 242 AS patients with reported ADC values on their initial mpMRI. ADC value from the index lesion was assessed as an independent predictor of GR using a Cox model. To ease clinical interpretation, we used a log-rank test to establish an ADC cutoff of 1128 × 10^-6 mm²/s for Kaplan-Meier analysis.

RESULTS

Of the 242 men, 70 underwent GR following initial mpMRI, of which 26 (37%) had GR at the index lesion. There was no significant difference in the median interval between biopsies for men with and without GR (P >.9). Men with GR had significantly lower median ADC than those without GR (P = .01). In multivariable analysis adjusting for age, prostate-specific antigen density, and National Comprehensive Cancer Network risk group, a 100-unit decrease in ADC was associated with a 12% increase in the risk of GR (HR = 1.12, 95% CI: 1.01-1.22, P = .03). Two- and 4-year rates of freedom from GR were significantly lower for men with ADC <1128 × 10^-6 mm²/s vs ADC ≥1128 × 10^-6 mm²/s (62% and 42% vs 78% and 68%, respectively; P <.001).

CONCLUSION

For AS patients, lower ADC on initial mpMRI index lesion is associated with increased risk of GR to GG ≥2 CaP and would be a useful component of multivariable risk prediction tools.

Active Surveillance of Grade Group 1 Prostate Cancer: Long-term Outcomes from a Large Prospective Cohort

BACKGROUND

Active surveillance (AS) is the preferred management option for most men with grade group (GG) 1 prostate cancer (PCa). Questions persist regarding long-term outcomes and the optimal approach to AS.

OBJECTIVE

To determine survival and metastatic outcomes in AS patients. Secondary objectives were to measure the cumulative incidence and association of patient-level factors on biopsy grade reclassification.

DESIGN, SETTING, AND PARTICIPANTS

A prospective, active, open-enrollment cohort study was conducted from 1995 through July 2018 at a tertiary-care academic institution. Patients with very-low-risk or low-risk PCa were enrolled.

INTERVENTION

AS with semiannual prostate-specific antigen (PSA) and digital rectal examination, serial prostate biopsy, and multiparametric magnetic resonance imaging (mpMRI).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The 10- and 15-yr cumulative incidences of primary and secondary outcomes were determined.

RESULTS AND LIMITATIONS

Overall, 1818 men were monitored on AS for a median of 5.0yr (interquartile range 2.0-9.0). There were 88 non-PCa deaths, four PCa deaths, and one additional case of metastasis. The cumulative incidence of PCa-specific mortality or metastasis was 0.1% (95% confidence interval, 0.04-0.6%) at both 10 and 15yr. The 5-, 10-, and 15-yr cumulative incidences of biopsy grade reclassification were 21%, 30%, and 32%, respectively. On multivariable analysis, biopsy grade reclassification was associated with older age, African-American race, PSA density, and increased cancer volume on biopsy, and men who underwent mpMRI prior to enrollment were less likely to undergo grade reclassification. Our selection and monitoring are more stringent than many other contemporary AS programs.

CONCLUSIONS

In a large, single-institution, prospective AS cohort, the risk of cancer death or metastasis was <1% over long-term follow-up. Consistent with clinical guidelines, these data support the use of AS for the management of most men diagnosed with GG1 PCa.

PATIENT SUMMARY

This study investigated long-term outcomes in patients with grade group 1 prostate cancer managed with active surveillance (AS). Ten years after enrolling in AS, the risk of metastasis or death from prostate cancer was <1%, while 48% of men switched to treatment. Patients who underwent multiparametric magnetic resonance imaging (mpMRI)/ultrasound-fusion targeted biopsy prior to enrollment were less likely to experience biopsy grade reclassification during follow-up, suggesting a role for mpMRI as part of a comprehensive risk assessment to confirm AS eligibility. These findings support the safety of AS in most men with grade group 1 prostate cancer, but specific outcomes may differ in programs with less intensive monitoring.

Tumor cell heterogeneity and resistance; report from the 2018 Coffey-Holden Prostate Cancer Academy Meeting

INTRODUCTION

The 2018 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, "Tumor Cell Heterogeneity and Resistance," was held in Los Angeles, California from June 21 to 24, 2018.

METHODS

The CHPCA Meeting is a unique, discussion-oriented scientific conference convened annually by the Prostate Cancer Foundation (PCF), which focuses on the most critical topics in need of further study to advance the treatment of lethal prostate cancer. The 6th Annual CHPCA Meeting was attended by 70 investigators and concentrated on prostate cancer heterogeneity and treatment resistance.

RESULTS

The meeting focused on topics including: recognition of tumor heterogeneity, molecular drivers of heterogeneity, the role of the tumor microenvironment, the role of heterogeneity in disease progression, metastasis and treatment resistance, clinical trials designed to target resistance and tumor heterogeneity, and immunotherapeutic approaches to target and overcome tumor heterogeneity.

DISCUSSION

This review article summarizes the presentations and discussions from the 2018 CHPCA Meeting in order to share this knowledge with the scientific community and encourage new studies that will lead to improved treatments and outcomes for men with prostate cancer.

epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer

Purpose

Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine.

Patients and Methods

Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set.

Results

Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy.

Conclusion

epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

Transcriptomic heterogeneity in multifocal prostate cancer

BACKGROUND

Commercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality.

METHODS

We designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared.

RESULTS

Derived expression scores were positively correlated with tumor grade (rS = 0.53-0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ≥GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (≥GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05).

CONCLUSIONS

Multifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease.

FUNDING

Prostate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

Utility of cell-free nucleic acid and circulating tumor cell analyses in prostate cancer

Prostate cancer is characterized by bone metastases and difficulty of objectively measuring disease burden. In this context, cell-free circulating tumor DNA (ctDNA) and circulating tumor cell (CTC) quantitation and genomic profiling afford the ability to noninvasively and serially monitor the tumor. Recent data suggest that ctDNA and CTC quantitation are prognostic for survival. Indeed, CTC enumeration using the CellSearch® platform is validated as a prognostic factor and warrants consideration as a stratification factor in randomized trials. Changes in quantities of CTCs using CellSearch also are prognostic and may be employed to detect a signal of activity of new agents. Molecular profiling of both CTCs and ctDNA for androgen receptor (AR) variants has been associated with outcomes in the setting of novel androgen inhibitors. Serial profiling to detect the evolution of new alterations may inform drug development and help develop precision medicine. The costs of these assays and the small quantities in which they are detectable in blood are a limitation, and novel platforms are required to address this challenge. The presence of multiple platforms to assay CTCs and ctDNA also warrants the consideration of a mechanism to allow comparison of data across platforms. Further validation and the continued development and standardization of these promising modalities will facilitate their adoption in the clinic.

Recent advances in the management of metastatic prostate cancer: optimizing use of existing therapies, while searching for novel interventions

PURPOSE OF REVIEW

Summarizes recent advances in the treatment of metastatic castration-sensitive and castration-resistant prostate cancer.

RECENT FINDINGS

New randomized data suggest a survival advantage to early abiraterone in castration-sensitive metastatic prostate cancer. Prospective and retrospective studies are examining sequencing of existing cytotoxic and androgen-receptor-targeted therapies in both castration-sensitive and castration-resistant disease. Genomic analysis of both circulating tumor cells and circulating tumor nucleic acids is being examined as a potential method for selecting existing therapies and identifying novel therapeutic targets. Finally, immunotherapy combinations are being evaluated in the setting of advanced prostate cancer.

SUMMARY

In this review, we hope to summarize the recent data supporting the use of early abiraterone in castration-sensitive metastatic prostate cancer and discuss how this data might be incorporated with previous trials showing a survival advantage to early docetaxel. We present recent series examining sequencing of approved therapies as well as trials evaluating novel biomarkers and genomic analyses designed to help choose from among approved therapies or evaluate drugs in development. Lastly, we review ongoing trials examining novel immunotherapy combinations in advanced prostate cancer.

Gene expression signatures of neuroendocrine prostate cancer and primary small cell prostatic carcinoma

Background

Neuroendocrine prostate cancer (NEPC) may be rising in prevalence as patients with advanced prostate cancer potentially develop resistance to contemporary anti-androgen treatment through a neuroendocrine phenotype. While prior studies comparing NEPC and prostatic adenocarcinoma have identified important candidates for targeted therapy, most have relied on few NEPC patients due to disease rarity, resulting in thousands of differentially expressed genes collectively and offering an opportunity for meta-analysis. Moreover, past studies have focused on prototypical NEPC samples with classic immunohistochemistry profiles, whereas there is increasing recognition of atypical phenotypes. In the primary setting, small cell prostatic carcinoma (SCPC) is frequently admixed with adenocarcinomas that may be clonally related, and a minority of SCPCs express markers typical of prostatic adenocarcinoma while rare cases do not express neuroendocrine markers. We derived a meta-signature of prototypical high-grade NEPC, then applied it to develop a classifier of primary SCPC incorporating disease heterogeneity.

Methods

Prototypical NEPC samples from 15 patients across 6 frozen tissue microarray datasets were assessed for genes with consistent outlier expression relative to adenocarcinomas. Resulting genes were used to determine subgroups of primary SCPCs (N=16) and high-grade adenocarcinomas (N=16) profiled by exon arrays using formalin-fixed paraffin-embedded (FFPE) material from our institutional archives. A subgroup classifier was developed using differential expression for feature selection, and applied to radical prostatectomy cohorts.

Results

Sixty nine and 375 genes demonstrated consistent outlier expression in at least 80% and 60% of NEPC patients, with close resemblance in expression between NEPC and small cell lung cancer. Clustering by these genes generated 3 subgroups among primary samples from our institution. Nearest centroid classification based on the predominant phenotype from each subgroup (9 prototypical SCPCs, 9 prototypical adenocarcinomas, and 4 atypical SCPCs) achieved a 4.5% error rate by leave-one-out cross-validation. The classifier identified SCPC-like expression in 40% (2/5) of mixed adenocarcinomas and 0.3-0.6% of adenocarcinomas from prospective (4/2293) and retrospective (2/355) radical prostatectomy cohorts, where both SCPC-like retrospective cases subsequently developed metastases.

Conclusions

Meta-analysis generates a robust signature of prototypical high-grade NEPC, and may facilitate development of a primary SCPC classifier based on FFPE material with potential prognostic implications.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3729-z) contains supplementary material, which is available to authorized users.

[Is there still a role for active surveillance in prostate cancer?]

Long-term data demonstrate a higher oncological risk associated with active surveillance (AS) than initially anticipated. In particular, patients with more than two tumor-involved biopsy cores and/or Gleason-7a foci must be regarded as having an increased risk of developing an incurable stage of disease after an initial attempt of AS. For patients with Gleason-7a foci, the 15-year risk of suffering from an incurable tumor stage is reported as high as 60%. Furthermore, life expectancy must be regarded as one of the major risk factors to finally develop symptomatic incurable disease. A discussion has therefore started as to whether a high life expectancy should be regarded as an exclusion criterion against AS. An estimated life expectancy exceeding 15 or 20 years has been proposed for patients suffering from Gleason 7a or 6 foci at initial biopsy, respectively. Furthermore, it must be expected that a number of molecular risk factors will gain importance in the near future for the decision-making process for or against AS.

Focal therapy in prostate cancer: A review of seven common controversies

Radical treatments such as prostatectomy and radiotherapy have demonstrated success in terms of biochemical and disease-specific survival for localised prostate cancer. However, whilst the end goal of any cancer treatment is to control or cure disease it must also do so by minimising any side effects that may be experienced by the patient. Focal therapy as a concept aims to redress this established therapeutic ratio by treating areas of the prostate affected by significant disease as opposed to treating the entire gland. However, there are a number of common criticisms of focal therapy - we deem the seven sins - that require further interrogation.

Integrated clinical, whole-genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

We report the first combined analysis of whole-genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole-genome and transcriptome sequence was obtained from nine anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 yr before death. Transcriptome analysis revealed increased expression of androgen receptor (AR)-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only one of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today, given this knowledge, the use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations may be critical for effective actionability and merit further study. Our findings suggest that a large set of deeply analyzed cases could serve as a powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools

Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5-6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with considerable morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.

Androgen receptor and prostate cancer stem cells: biological mechanisms and clinical implications

Prostate cancer (PCa) contains phenotypically and functionally distinct cells, and this cellular heterogeneity poses clinical challenges as the distinct cell types likely respond differently to various therapies. Clonal evolution, driven by genetic instability, and intraclonal cancer cell diversification, driven by cancer stem cells (CSCs), together create tumor cell heterogeneity. In this review, we first discuss PCa stem cells (PCSCs) and heterogeneity of androgen receptor (AR) expression in primary, metastatic, and treatment-failed PCa. Based on literature reports and our own studies, we hypothesize that, whereas PCSCs in primary and untreated tumors and models are mainly AR(-), PCSCs in CRPCs could be either AR(+) or AR(-/lo). We illustrate the potential mechanisms AR(+) and AR(-) PCSCs may employ to propagate PCa at the population level, mediate therapy resistance, and metastasize. As a result, targeting AR alone may not achieve long-lasting therapeutic efficacy. Elucidating the roles of AR and PCSCs should provide important clues to designing novel personalized combinatorial therapeutic protocols targeting both AR(+) and AR(-) PCa cells.

Evaluation of an epithelial plasticity biomarker panel in men with localized prostate cancer

BACKGROUND

Given the potential importance of epithelial plasticity (EP) to cancer metastasis, we sought to investigate biomarkers related to EP in men with localized prostate cancer (PC) for the association with time to PSA recurrence and other clinical outcomes after surgery.

METHODS

Men with localized PC treated with radical prostatectomy at the Durham VA Medical Center and whose prostatectomy tissues were included in a tissue microarray (TMA) linked to long-term outcomes. We performed immunohistochemical studies using validated antibodies against E-cadherin and Ki-67 and mesenchymal biomarkers including N-cadherin, vimentin, SNAIL, ZEB1 and TWIST. Association studies were conducted for each biomarker with baseline clinical/pathologic characteristics an risk of PSA recurrence over time.

RESULTS

Two hundred and five men contributed TMA tissue and had long-term follow-up (median 11 years). Forty-three percent had PSA recurrence; three died of PC. The majority had high E-cadherin expression (86%); 14% had low/absent E-cadherin expression. N-cadherin was rarely expressed (<4%) and we were unable to identify an E-to-N-cadherin switch as independently prognostic. No associations with clinical risk group, PSA recurrence or Gleason sum were noted for SNAIL, ZEB1, vimentin or TWIST, despite heterogeneous expression between patients. We observed an association of higher Ki-67 expression with Gleason sum (P=0.043), National Comprehensive Cancer Network risk (P=0.013) and PSA recurrence (hazard ratio 1.07, P=0.016).

CONCLUSIONS

The expression of EP biomarkers in this cohort of men with a low risk of PC-specific mortality was not associated with aggressive features or PSA relapse after surgery.

Cyclin D1 Loss Distinguishes Prostatic Small-Cell Carcinoma from Most Prostatic Adenocarcinomas

PURPOSE

Small-cell neuroendocrine differentiation in prostatic carcinoma is an increasingly common resistance mechanism to potent androgen deprivation therapy (ADT), but can be difficult to identify morphologically. We investigated whether cyclin D1 and p16 expression can inform on Rb functional status and distinguish small-cell carcinoma from adenocarcinoma.

EXPERIMENTAL DESIGN

We used gene expression data and immunohistochemistry to examine cyclin D1 and p16 levels in patient-derived xenografts (PDX), and prostatic small-cell carcinoma and adenocarcinoma specimens.

RESULTS

Using PDX, we show proof-of-concept that a high ratio of p16 to cyclin D1 gene expression reflects underlying Rb functional loss and distinguishes morphologically identified small-cell carcinoma from prostatic adenocarcinoma in patient specimens (n = 13 and 9, respectively). At the protein level, cyclin D1, but not p16, was useful to distinguish small-cell carcinoma from adenocarcinoma. Overall, 88% (36/41) of small-cell carcinomas showed cyclin D1 loss by immunostaining compared with 2% (2/94) of Gleason score 7-10 primary adenocarcinomas at radical prostatectomy, 9% (4/44) of Gleason score 9-10 primary adenocarcinomas at needle biopsy, and 7% (8/115) of individual metastases from 39 patients at autopsy. Though rare adenocarcinomas showed cyclin D1 loss, many of these were associated with clinical features of small-cell carcinoma, and in a cohort of men treated with adjuvant ADT who developed metastasis, lower cyclin D1 gene expression was associated with more rapid onset of metastasis and death.

CONCLUSIONS

Cyclin D1 loss identifies prostate tumors with small-cell differentiation and may identify a small subset of adenocarcinomas with poor prognosis. Clin Cancer Res; 21(24); 5619-29. ©2015 AACR.

Active surveillance and focal therapy for low-intermediate risk prostate cancer

Low risk and many cases of low-intermediate risk prostate cancer, are indolent, have little or no metastatic potential, and are not life threatening. Major advances have been made in understanding who these patients are, and in encouraging the use of conservative management in such individuals. Conservative management incorporates the early identification of those 'low risk' patients who harbor higher risk disease, and benefit from definitive therapy. Based on the current algorithm of PSA followed by systematic biopsy, this represents about 30% of newly diagnosed low risk patients. A further small proportion of patients with low risk disease demonstrate biological progression to higher grade disease. Men with lower risk disease can defer treatment, usually for life. Men with higher risk disease that can be localized to a relatively small volume of the prostate may be candidates for focal, prostate sparing therapy. The results of active surveillance, embodying conservative management with selective delayed intervention for the subset who are re-classified as higher risk over time based on repeat biopsy, imaging, or biomarker results, have shown that this approach is safe in the intermediate to long term, with a 1-5% cancer specific mortality at 15 years. Further refinement of the surveillance approach is ongoing, incorporating MRI, targeted biopsies, and molecular biomarkers.

Detecting predictive androgen receptor modifications in circulating prostate cancer cells

Molecular modifications of the androgen receptor (AR) can cause resistance to androgen deprivation therapy (ADT) in prostate cancer patients. Since lack of representative tumor samples hinders therapy adjustments according to emerging AR-modifications, we evaluated simultaneous detection of the two most common AR modifications (AR-V7 splice variant and AR point mutations) in circulating tumor cells (CTCs). We devised a single-tube assay to detect AR-V7 splice variants and AR point mutations in CTCs using immunomagnetic cell isolation, followed by quantitative real-time PCR and DNA pyrosequencing. We prospectively investigated 47 patients with PSA progression awaiting therapy switch. Comparison of response to newly administered therapy and CTC-AR-status allowed effect size estimation. Nineteen (51%) of 37 patients with detectable CTCs carried AR-modifications. Seventeen patients carried the AR-V7 splice variant, one harbored a p.T878A point mutation and one harbored both AR-V7 and a p.H875Y mutation. We estimated a positive predictive value for response and non-response to therapy by AR status in CTCs of ~94%. Based on a conservative calculation, we estimated the effect size for molecularly-informed therapy switches for prospective clinical trial planning to ~27%. In summary, the ability to determine key resistance-mediating AR modifications in CTCs has the potential to considerably improve prostate cancer treatment.

Untreated Gleason Grade Progression on Serial Biopsies during Prostate Cancer Active Surveillance: Clinical Course and Pathological Outcomes

PURPOSE

We describe the outcomes of patients with low risk localized prostate cancer who were upgraded on a surveillance biopsy while on active surveillance and evaluated whether delayed treatment was associated with adverse outcome.

MATERIALS AND METHODS

We included men in the study with lower risk disease managed initially with active surveillance and upgraded to Gleason score 3+4 or greater. Patient demographics and disease characteristics were compared. Kaplan-Meier curve was used to estimate the treatment-free probability stratified by initial upgrade (3+4 vs 4+3 or greater), Cox regression analysis was used to examine factors associated with treatment and multivariate logistic regression analysis was used to evaluate the factors associated with adverse outcome at surgery.

RESULTS

The final cohort comprised 219 men, with 150 (68%) upgraded to 3+4 and 69 (32%) to 4+3 or greater. Median time to upgrade was 23 months (IQR 11-49). A total of 163 men (74%) sought treatment, the majority (69%) with radical prostatectomy. The treatment-free survival rate at 5 years was 22% for 3+4 and 10% for 4+3 or greater upgrade. Upgrade to 4+3 or greater, higher prostate specific antigen density at diagnosis and shorter time to initial upgrade were associated with treatment. At surgical pathology 34% of cancers were downgraded while 6% were upgraded. Cancer volume at initial upgrade was associated with adverse pathological outcome at surgery (OR 3.33, 95% CI 1.19-9.29, p=0.02).

CONCLUSIONS

After Gleason score upgrade most patients elected treatment with radical prostatectomy. Among men who deferred definitive intervention, few experienced additional upgrading. At radical prostatectomy only 6% of cases were upgraded further and only tumor volume at initial upgrade was significantly associated with adverse pathological outcome.

Will active surveillance for clinically localized prostate cancer survive in the era of individualized medicine?

The challenge for the next few years will be to individualize prostate cancer treatment and to determine whether or not a cancer will be lethal based on molecular characteristics at the time of diagnosis. In this view, the need for active treatment would represent a failure of any conservative approach.