Active surveillance for prostate cancer: past, present and future

Genomics in active surveillance and post-prostatectomy patients: A review of when and how to use effectively

PURPOSE OF REVIEW

Prostate cancer (PCa) represents a significant health burden globally, ranking as the most diagnosed cancer among men and a leading cause of cancer-related mortality. Conventional treatment methods such as radiation therapy or radical prostatectomy have significant side effects which often impact quality of life. As our understanding of the natural history and progression of PCa has evolved, so has the evolution of management options.

RECENT FINDINGS

Active surveillance (AS) has become an increasingly favored approach to the management of very low, low, and properly selected favorable intermediate risk PCa. AS permits ongoing observation and postpones intervention until definitive treatment is required. There are, however, challenges with selecting patients for AS, which further emphasizes the need for more precise tools to better risk stratify patients and choose candidates more accurately. Tissue-based biomarkers, such as ProMark, Prolaris, GPS (formerly Oncotype DX), and Decipher, are valuable because they improve the accuracy of patient selection for AS and offer important information on the prognosis and severity of disease. By enabling patients to be categorized according to their risk profiles, these biomarkers help physicians and patients make better informed treatment choices and lower the possibility of overtreatment. Even with their potential, further standardization and validation of these biomarkers is required to guarantee their broad clinical utility. Active surveillance has emerged as a preferred strategy for managing low-risk prostate cancer, and tissue-based biomarkers play a crucial role in refining patient selection and risk stratification. Standardization and validation of these biomarkers are essential to ensure their widespread clinical use and optimize patient outcomes.

Spatial Profiling of the Prostate Cancer Tumor Microenvironment Reveals Multiple Differences in Gene Expression and Correlation with Recurrence Risk

The tumor microenvironment plays a crucial role in both the development and progression of prostate cancer. Furthermore, identifying protein and gene expression differences between different regions is valuable for treatment development. We applied Digital Spatial Profiling multiplex analysis to formalin-fixed paraffin embedded prostatectomy tissue blocks to investigate protein and transcriptome differences between tumor, tumor-adjacent stroma (TAS), CD45+ tumor, and CD45+ TAS tissue. Differential expression of an immunology/oncology protein panel (n = 58) was measured. OX40L and CTLA4 were expressed at higher levels while 22 other proteins, including CD11c, were expressed at lower levels (FDR < 0.2 and p-value < 0.05) in TAS as compared to tumor epithelia. A tissue microarray analysis of 97 patients with 1547 cores found positive correlations between high expression of CD11c and increased time to recurrence in tumor and TAS, and inverse relationships for CTLA4 and OX40L, where higher expression in tumor correlated with lower time to recurrence, but higher time to recurrence in TAS. Spatial transcriptomic analysis using a Cancer Transcriptome Atlas panel (n = 1825 genes) identified 162 genes downregulated and 69 upregulated in TAS versus tumor, 26 downregulated and 6 upregulated in CD45+ TAS versus CD45+ tumor. We utilized CIBERSORTx to estimate the relative immune cell fractions using CD45+ gene expression and found higher average fractions for memory B, naïve B, and T cells in TAS. In summary, the combination of protein expression differences, immune cell fractions, and correlations of protein expression with time to recurrence suggest that closely examining the tumor microenvironment provides valuable data that can improve prognostication and treatment techniques.

Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound

Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.

Recurrence analysis on prostate cancer patients with Gleason score 7 using integrated histopathology whole-slide images and genomic data through deep neural networks

Prostate cancer is the most common nonskin-related cancer, affecting one in seven men in the United States. Gleason score, a sum of the primary and secondary Gleason patterns, is one of the best predictors of prostate cancer outcomes. Recently, significant progress has been made in molecular subtyping prostate cancer through the use of genomic sequencing. It has been established that prostate cancer patients presented with a Gleason score 7 show heterogeneity in both disease recurrence and survival. We built a unified system using publicly available whole-slide images and genomic data of histopathology specimens through deep neural networks to identify a set of computational biomarkers. Using a survival model, the experimental results on the public prostate dataset showed that the computational biomarkers extracted by our approach had hazard ratio as 5.73 and C -index as 0.74, which were higher than standard clinical prognostic factors and other engineered image texture features. Collectively, the results of this study highlight the important role of neural network analysis of prostate cancer and the potential of such approaches in other precision medicine applications.

Prostate-Associated Gene 4 (PAGE4): Leveraging the Conformational Dynamics of a Dancing Protein Cloud as a Therapeutic Target

Prostate cancer (PCa) is a leading cause of mortality and morbidity globally. While genomic alterations have been identified in PCa, in contrast to some other cancers, use of such information to personalize treatment is still in its infancy. Here, we discuss how PAGE4, a protein which appears to act both as an oncogenic factor as well as a metastasis suppressor, is a novel therapeutic target for PCa. Inhibiting PAGE4 may be a viable strategy for low-risk PCa where it is highly upregulated. Conversely, PAGE4 expression is downregulated in metastatic PCa and, therefore, reinstituting its sustained expression may be a promising option to subvert or attenuate androgen-resistant PCa. Thus, fine-tuning the levels of PAGE4 may represent a novel approach for personalized medicine in PCa.

Urinary CE-MS peptide marker pattern for detection of solid tumors

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.

Stochastic Modeling of Temporal Enhanced Ultrasound: Impact of Temporal Properties on Prostate Cancer Characterization

OBJECTIVES

Temporal enhanced ultrasound (TeUS) is a new ultrasound-based imaging technique that provides tissue-specific information. Recent studies have shown the potential of TeUS for improving tissue characterization in prostate cancer diagnosis. We study the temporal properties of TeUS-temporal order and length-and present a new framework to assess their impact on tissue information.

METHODS

We utilize a probabilistic modeling approach using hidden Markov models (HMMs) to capture the temporal signatures of malignant and benign tissues from TeUS signals of nine patients. We model signals of benign and malignant tissues (284 and 286 signals, respectively) in their original temporal order as well as under order permutations. We then compare the resulting models using the Kullback-Liebler divergence and assess their performance differences in characterization. Moreover, we train HMMs using TeUS signals of different durations and compare their model performance when differentiating tissue types.

RESULTS

Our findings demonstrate that models of order-preserved signals perform statistically significantly better (85% accuracy) in tissue characterization compared to models of order-altered signals (62% accuracy). The performance degrades as more changes in signal order are introduced. Additionally, models trained on shorter sequences perform as accurately as models of longer sequences.

CONCLUSION

The work presented here strongly indicates that temporal order has substantial impact on TeUS performance; thus, it plays a significant role in conveying tissue-specific information. Furthermore, shorter TeUS signals can relay sufficient information to accurately distinguish between tissue types.

SIGNIFICANCE

Understanding the impact of TeUS properties facilitates the process of its adopting in diagnostic procedures and provides insights on improving its acquisition.

Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers

Previous studies have reported association of multiple preoperative factors predicting clinically significant prostate cancer with varying results. We assessed the predictive model using a combination of hormone profile, serum biomarkers, and patient characteristics in order to improve the accuracy of risk stratification of patients with prostate cancer. Data on 224 patients from our prostatectomy database were queried. Demographic characteristics, including age, body mass index (BMI), clinical stage, clinical Gleason score (GS) as well as serum biomarkers, such as prostate-specific antigen (PSA), parathyroid hormone (PTH), calcium (Ca), prostate acid phosphatase (PAP), testosterone, and chromogranin A (CgA), were used to build a predictive model of clinically significant prostate cancer using logistic regression methods. We assessed the utility and validity of prediction models using multiple 10-fold cross-validation. Bias-corrected area under the receiver operating characteristics (ROC) curve (bAUC) over 200 runs was reported as the predictive performance of the models. On univariate analyses, covariates most predictive of clinically significant prostate cancer were clinical GS (OR 5.8, 95% CI 3.1–10.8; P < 0.0001; bAUC = 0.635), total PSA (OR 1.1, 95% CI 1.06–1.2; P = 0.0003; bAUC = 0.656), PAP (OR 1.5, 95% CI 1.1–2.1; P = 0.016; bAUC = 0.583), and BMI (OR 1.064, 95% C.I. 0.998, 1.134; P < 0.056; bAUC = 0.575). On multivariate analyses, the most predictive model included the combination of preoperative PSA, prostate weight, clinical GS, BMI and PAP with bAUC 0.771 ([2.5, 97.5] percentiles = [0.76, 0.78]). Our model using preoperative PSA, clinical GS, BMI, PAP, and prostate weight may be a tool to identify individuals with adverse oncologic characteristics and classify patients according to their risk profiles.

Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations

PURPOSE  : Temporal Enhanced Ultrasound (TeUS) has been proposed as a new paradigm for tissue characterization based on a sequence of ultrasound radio frequency (RF) data. We previously used TeUS to successfully address the problem of prostate cancer detection in the fusion biopsies. METHODS  : In this paper, we use TeUS to address the problem of grading prostate cancer in a clinical study of 197 biopsy cores from 132 patients. Our method involves capturing high-level latent features of TeUS with a deep learning approach followed by distribution learning to cluster aggressive cancer in a biopsy core. In this hypothesis-generating study, we utilize deep learning based feature visualization as a means to obtain insight into the physical phenomenon governing the interaction of temporal ultrasound with tissue. RESULTS  : Based on the evidence derived from our feature visualization, and the structure of tissue from digital pathology, we build a simulation framework for studying the physical phenomenon underlying TeUS-based tissue characterization. CONCLUSION  : Results from simulation and feature visualization corroborated with the hypothesis that micro-vibrations of tissue microstructure, captured by low-frequency spectral features of TeUS, can be used for detection of prostate cancer.

Clinical Predictors of Fatigue in Men With Non-Metastatic Prostate Cancer Receiving External Beam Radiation Therapy

BACKGROUND

Fatigue is one of the most distressing symptoms experienced by people with cancer receiving radiation therapy.

OBJECTIVES

The goal of this study is to evaluate clinical predictors of worsening fatigue during external beam radiation therapy (EBRT) in men with non-metastatic prostate cancer.

METHODS

Thirty-five men with non-metastatic prostate cancer scheduled for EBRT were followed at baseline, midpoint, and completion of EBRT. The Functional Assessment of Cancer Therapy-Fatigue scale was administered. Demographic and clinical data were obtained by chart review. Paired t-tests, correlations, general linear models, and logistic regressions were used to determine associations between fatigue scores and clinical data.

FINDINGS

Red blood cells, hemoglobin, and hematocrit levels were highly intercorrelated and, therefore, were grouped as one composite variable termed heme. Heme levels at baseline and androgen-deprivation therapy (ADT) were significantly correlated with worsening of fatigue symptoms from baseline to midpoint and endpoint. ADT alone did not have a significant correlation with fatigue, but it indirectly affected fatigue levels by influencing heme markers as treatment progressed. These findings provide evidence that hematologic markers and the use of ADT assist in predicting radiation therapy-related fatigue and guide symptom management.

The role of MRI in active surveillance for prostate cancer

Approximately one in seven American men will be diagnosed with prostate cancer during his lifetime, and at least 50% of newly diagnosed patients will present with low-risk disease. In the last decade, the decision-making paradigm for management has shifted due to high rates of disease detection and overtreatment, attributed to prostate-specific antigen screening, with more men deferring definitive treatment for active surveillance. The advent of multiparametric magnetic resonance imaging (MP-MRI) and MRI/ transrectal ultrasound-guided fusion-guided prostate biopsy has refined the process of diagnosis, identifying patients with clinically-significant cancer and larger disease burden who would most likely benefit from intervention. In parallel, the utilization of MP-MRI in the surveillance of low-grade, low-volume disease is on the rise, reflecting support in a growing body of literature. The aim of this review is to appraise and summarize the data evaluating the role of magnetic resonance imaging in active surveillance for prostate cancer.

Clonal evaluation of prostate cancer foci in biopsies with discontinuous tumor involvement by dual ERG/SPINK1 immunohistochemistry

The presence of two or more prostate cancer foci separated by intervening benign tissue in a single core is a well-recognized finding on prostate biopsy. Cancer involvement can be measured by including intervening benign tissue or only including the actual cancer involved area. Importantly, this parameter is a common enrollment criterion for active surveillance protocols. We hypothesized that spatially distinct prostate cancer foci in biopsies may arise from separate clones, impacting cancer involvement assessment. Hence, we used dual ERG/SPINK1 immunohistochemistry to determine the frequency of separate clones-when separate tumor foci showed discordant ERG and/or SPINK1 status-in discontinuously involved prostate biopsy cores from two academic institutions. In our cohort of 97 prostate biopsy cores with spatially discrete tumor foci (from 80 patients), discontinuous cancer involvement including intervening tissue ranged from 20 to 100% and Gleason scores ranged from 6 to 9. Twenty-four (25%) of 97 discontinuously involved cores harbored clonally distinct cancer foci by discordant ERG and/or SPINK1 expression status: 58% (14/24) had one ERG(+) focus, and one ERG(-)/SPINK1(-) focus; 29% (7/24) had one SPINK1(+) focus and one ERG(-)/SPINK1(-) focus; and 13% (3/24) had one ERG(+) focus and one SPINK1(+) focus. ERG and SPINK1 overexpression were mutually exclusive in all tumor foci. In summary, our results show that ~25% of discontinuously involved prostate biopsy cores showed tumor foci with discordant ERG/SPINK1 status, consistent with multiclonal disease. The relatively frequent presence of multiclonality in discontinuously involved prostate biopsy cores warrants studies on the potential clinical impact of clonality assessment, particularly in cases where tumor volume in a discontinuous core may impact active surveillance eligibility.

Preliminary results of the Spanish Association of Urology National Registry in Active Surveillance for prostate cancer

OBJECTIVES

To present a National Registry of patients with prostate cancer as monitored through active surveillance, with the intention of testing the hypothesis that cancer-specific mortality in very low-risk and low-risk patients is less than 5% at 15 years.

MATERIAL AND METHODS

A multicentre observational study (AEU-PIEM/2014/0001) sponsored by the Spanish Association of Urology was conducted using their platform for multicentre studies. The clinical-pathological inclusion criteria were as follows: cT1a-cT3a, PSA ≤ 20 ng/ml, initial minimum biopsy of 10 cores, number of affected cores ≤ 3, 1st Gleason score of 3 and 2nd Gleason score ≤ 4 and a known prostate volume (in cc). A unified follow-up was not established for all recruiting centres; however, a survey was conducted that reflects the follow-up characteristics based on a number of tangible parameters that allow for their comparison. With the same philosophy of flexibility, the use of certain biomarkers and multiparametric MRI was not considered necessary for inclusion.

RESULTS

We describe the Registry's characteristics and possibilities, as well as the preliminary results from the 324 patients included in its first 5 months of operation in the 15 recruiting centres. We also report the clinical-pathological variables, biomarkers, radiodiagnosis technique and quality-of-life questionnaires considered for the database, as well as the possibilities for indefinite follow-up, remaining open to any active treatment recognized in clinical guidelines.

CONCLUSIONS

The AEU-PIEM/2014/0001 represents an extremely useful tool for all Spanish urologists for multicentre clinical research. The registry will undoubtedly enable the dissemination of active surveillance of our patients in a more coordinated manner, thus maintaining the advantages of optimised opportunistic screening for prostate cancer without resulting in overtreatment.

Interactive Feature Space Explorer© for multi-modal magnetic resonance imaging

Wider information content of multi-modal biomedical imaging is advantageous for detection, diagnosis and prognosis of various pathologies. However, the necessity to evaluate a large number images might hinder these advantages and reduce the efficiency. Herein, a new computer aided approach based on the utilization of feature space (FS) with reduced reliance on multiple image evaluations is proposed for research and routine clinical use. The method introduces the physician experience into the discovery process of FS biomarkers for addressing biological complexity, e.g., disease heterogeneity. This, in turn, elucidates relevant biophysical information which would not be available when automated algorithms are utilized. Accordingly, the prototype platform was designed and built for interactively investigating the features and their corresponding anatomic loci in order to identify pathologic FS regions. While the platform might be potentially beneficial in decision support generally and specifically for evaluating outlier cases, it is also potentially suitable for accurate ground truth determination in FS for algorithm development. Initial assessments conducted on two different pathologies from two different institutions provided valuable biophysical perspective. Investigations of the prostate magnetic resonance imaging data resulted in locating a potential aggressiveness biomarker in prostate cancer. Preliminary findings on renal cell carcinoma imaging data demonstrated potential for characterization of disease subtypes in the FS.

Relationship between illness uncertainty, anxiety, fear of progression and quality of life in men with favourable-risk prostate cancer undergoing active surveillance

OBJECTIVES

To evaluate prospectively the associations between illness uncertainty, anxiety, fear of progression and general and disease-specific quality of life (QoL) in men with favourable-risk prostate cancer undergoing active surveillance (AS).

PATIENTS AND METHODS

After meeting stringent enrollment criteria for an AS cohort study at a single tertiary care cancer centre, 180 men with favourable-risk prostate cancer completed questionnaires at the time of enrollment and every 6 months for up to 30 months. Questionnaires assessed illness uncertainty, anxiety, prostate-specific QoL (using the Expanded Prostate Cancer Index Composite [EPIC] scale) and general QoL (using the 12-time short-form health survey [SF-12]) and fear of progression. We used linear mixed-model analyses and multilevel mediation analyses.

RESULTS

Sexual scores on the EPIC scale significantly declined over time (P < 0.05). Illness uncertainty was a significant predictor of all EPIC summary scores, SF-12 physical component summary (PCS) scores, mental component summary (MCS) scores and fear of progression scores (all P < 0.05), after controlling for demographic and clinicopathological factors. Anxiety predicted all EPIC summary, MCS and fear of progression scores (all P < 0.05) but not PCS scores (P = 0.08). Scores on PCS, MCS, EPIC summary scales (except sexual scale), and fear of progression did not change significantly over the study period (all P > 0.10).

CONCLUSION

Over the 2.5-year follow-up, QoL remained stable; only sexual function scores significantly declined. Illness uncertainty and anxiety were significant predictors of general and prostate-specific QoL and fear of progression. Interventions to reduce uncertainty and anxiety may enhance QoL for men with prostate cancer on AS.

Development and preliminary testing of PROGRESS: a Web-based education program for prostate cancer survivors transitioning from active treatment

PURPOSE

This formative research study describes the development and preliminary evaluation of a theory-guided, online multimedia psycho-educational program (PROGRESS) designed to facilitate adaptive coping among prostate cancer patients transitioning from treatment into long-term survivorship.

METHODS

Guided by the Cognitive-Social Health Information Processing Model (C-SHIP) and using health communications best practices, we conducted a two-phase, qualitative formative research study with early stage prostate cancer patients (n = 29) to inform the Web program development. Phase 1 included individual (n = 5) and group (n = 12) interviews to help determine intervention content and interface. Phase 2 employed iterative user/usability testing (n = 12) to finalize the intervention. Interview data were independently coded and collectively analyzed to achieve consensus.

RESULTS

Survivors expressed interest in action-oriented content on (1) managing treatment side effects, (2) handling body image and comorbidities related to overweight/obesity, (3) coping with emotional and communication issues, (4) tips to reduce disruptions of daily living activities, and (5) health skills training tools. Patients also desired the use of realistic and diverse survivor images.

CONCLUSIONS

Incorporation of an established theoretical framework, application of multimedia intervention development best practices, and an evidence-based approach to content and format resulted in a psycho-educational tool that comprehensively addresses survivors' needs in a tailored fashion.

IMPLICATIONS FOR CANCER SURVIVORS

The results suggest that an interactive Web-based multimedia program is useful for survivors if it covers the key topics of symptom control, emotional well-being, and coping skills training; this tool has the potential to be disseminated and implemented as an adjunct to routine clinical care.

Does cumulative prostate cancer length (CCL) in prostate biopsies improve prediction of clinically insignificant cancer at radical prostatectomy in patients eligible for active surveillance?

OBJECTIVES

To evaluate if cumulative prostate cancer length (CCL) on prostate needle biopsy divided by the number of biopsy cores (CCL/core) could improve prediction of insignificant cancer on radical prostatectomy (RP) in patients with prostate cancer eligible for active surveillance (AS).

PATIENTS AND METHODS

Patients diagnosed with prostate cancer on extended (≥10 cores) biopsy with an initial prostate-specific antigen (iPSA) level of <15 ng/mL, clinical stage (cT) ≤ 2a, and highest biopsy Gleason score 3 + 3 = 6 or 3 + 4 = 7 with <3 positive cores who underwent RP were included in the study. The CCL/core and presence of insignificant cancer (organ-confined, volume <0.5 mL, Gleason score at RP ≤6) were recorded. pT2 prostate cancer with RP Gleason score ≤3 + 4 = 7 and volume <0.5 mL were categorised as low-tumour-volume organ-confined disease (LV-OCD).

RESULTS

In all, 221 patients met the inclusion criteria: the mean age was 59 years and the median iPSA level was 4.5 ng/mL. The clinical stage was cT1 in 86% of patients; biopsy Gleason score was 3 + 3 = 6 in 67% (group 1) and 3 + 4 = 7 in 33% of patients (group 2). The maximum percentage of biopsy core involvement was <50 in 85%; the median CCL/core was 0.15 mm. Insignificant cancer was found in 27% and LV-OCD in 44% of patients. Group 2 was associated with higher number of positive cores, maximum percentage core involvement, total prostate cancer length, and CCL/core. Group 1 was more likely to have insignificant cancer (39%) or LV-OCD (54%) than group 2 (3% and 23%, respectively). Group 2 had significantly higher RP Gleason score and pathological stage. Univariate analysis of group 1 showed that the iPSA level, maximum percentage core involvement, prostate cancer length, and CCL/core were all significantly associated with insignificant cancer and LV-OCD. For group 2, the number of positive cores (1 vs 2) was also significantly associated with LV-OCD. On multivariate logistic regression analysis, maximum percentage core involvement of <50, and number of positive cores (1 vs 2) were independent predictors of insignificant cancer in group 1; biopsy Gleason score, maximum percentage core involvement of <50 and prostate cancer length of <3 mm or CCL/core of <0.2 mm were all independent predictors of LV-OCD in the whole population. The maximum percentage of core involvement of <50 and prostate cancer length of <3 mm or CCL/core of <0.2 mm were also independent predictors of LV-OCD in group 1 patients.

CONCLUSION

In patients eligible for AS, a CCL/core of <0.20 mm was significantly associated with insignificant cancer and LV-OCD. However, when parameters of cancer burden were considered, CCL/core did not independently add any additional value for predicting insignificant cancer in patients with biopsy Gleason score 6. The CCL/core was an independent predictor of LV-OCD in the whole population and in group 1 patients, although the model including prostate cancer length showed slightly higher area under the receiver operating characteristic curve.

Obligatory information that a patient diagnosed of prostate cancer and candidate for an active surveillance protocol must know

OBJECTIVES

To know the necessary information to reproduce the results found in the literature on active surveillance (AS) in prostate cancer (PCa) in our own center so that the information would be objective and correctly given to the patients. We have aimed to study the percentage of candidates for AS chosen in our setting, and the data on infrastaging, subgrading and prediction of insignificant PCa, debugging the predictive value of clinical variables to improve our selection criteria and finally to analyze the results of our patients enrolled in AS.

MATERIALS AND METHODS

A retro- and prospective review of our data bases was performed. A one-year period was analyzed to know AS candidates. Analysis of our radical prostatectomy specimens for infrastaging, subgrading and prediction of insignificant PCa (Epstein's criteria) was made as well as a uni/multivariate analysis of clinical variables in patients with insignificant PCa in the specimen. A prospective validation was performed with overall survival and survival free of active treatment (SFAT) as endpoints in patients enrolled in AS.

RESULTS

Between October-2010/October-2011, 44.7% of our PCa were candidates for AS, but only 11.2% choose it. The percentages found for infrastaging, subgrading and prediction of insignificant PCa were 14%, 31.4% and 55.7%, respectively. However, only just 6 patients (6.97%) had≥pT3a+Gleason≥7+volume>0.5cc PCa. The multivariate analysis showed that PSA density and number of affected cores were independent predictors of insignificant PCa. With a mean follow-up of 36±39months, 63 out of 232 patients enrolled in AS went on to active treatment (27.1%), with only 13 due to anxiety without pathologic progression. Median time of SFAT was 72.7 months (CI 95% 30.9-114.4). SFAT at 24 months was 76.4% (69.7-83.1%) and at 48 months 58.1% (48.8-67.4%). Only 10 patients died (4.3%), 9 due to causes different of PCa. Estimated overall survival at 5 years was 92.8% (CI 95% 86.7-98.9%).

CONCLUSIONS

It should be mandatory to have the exact knowledge of the local data of each Center in order to objectively inform patients about prostate biopsy efficiency, and if percentages of infrastaging, subgrading and prediction of insignificant PCa are in accordance with the literature. At 3 years, we reproduced the results of the longest series of AS, so we have ascertained that our AS protocol can be implemented with increasingly more patients.

Prostate cancer: a review of active surveillance

The objective of this paper is to review the current recommendations for active surveillance in prostate cancer from the present prospective studies. Worldwide, there are increasing numbers of men with prostate cancer. It is now accepted as standard care that a number of men with favorable-risk disease can be followed with active surveillance. In 1995, the first prospective studies were initiated to assess the feasibility of active surveillance, in which the decision to intervene was determined by prostate-specific antigen and/or histological progression. The strategy was to provide therapy individualized to the biological behavior of the cancer. Clinical trials assessing active surveillance have usually included patients younger than 70 years of age, although the guidelines have changed over time for Gleason score and prostate-specific antigen, eg, doubling time, thereby changing the indication for active treatment. The present review focuses on patient selection, prospective studies reported in the literature, and future directions.

Prostate cancer prevention: agent development strategies

Despite advances in surgery, radiation, and medical therapy over the past decade and the widespread adoption of PSA screening, prostate cancer continues to be the second leading cause of cancer death in men in the United States. Invasive cancer is the end result of carcinogenesis, a chronic process occurring over many years driven by genetic and epigenetic alterations. The protracted nature of this transformation to the malignant phenotype provides an opportunity to intervene pharmacologically to prevent, reverse, or delay carcinogenesis, i.e. chemoprevention. Herein, we describe the unique features of cancer prevention, as opposed to cancer treatment, agent development clinical trials, and provide a summary of the ongoing research in this field being supported by the National Cancer Institute.

Role of high-field MR in studies of localized prostate cancer

Magnetic resonance imaging is attracting increasing attention from the uroradiological community as a modality to guide the management of prostate cancer. With the high incidence of prostate cancer it might come as a surprise that for a very long time (and in many places even at present) treatment decisions were being made without the use of detailed anatomical and functional imaging of the prostate gland at hand. Although T2 -weighted MRI can provide great anatomical detail, by itself it is not specific enough to discriminate cancer from benign disease, so other functional MRI techniques have been explored to aid in detection, localization, staging and risk assessment of prostate cancer. With the current evolution of clinical MR systems from 1.5 to 3 T it is important to understand the advantages and the challenges of the higher magnetic field strength for the different functional MR techniques most used in the prostate: T2 -weighted MRI, diffusion-weighted MRI, MR spectroscopic imaging and dynamic contrast-enhanced imaging. In addition to this, the use of the endorectal coil at different field strengths is discussed in this review, together with an outlook of the possibilities of ultra-high-field MR for the prostate.

Predicting high risk disease using serum and DNA biomarkers

PURPOSE OF REVIEW

To explore several serum and genetic-based biomarkers that may prove useful in following men being managed with active surveillance for localized prostate cancer by predicting those that either have the potential to develop, or already harbor occult high grade disease.

RECENT FINDINGS

There is increasing evidence that serum biomarkers human Kallikrein 2, early prostate cancer antigen, urokinase-type plasminogen activator/urokinase-type plasminogen activator receptor, transforming growth factor-β1 and interleukin-6/interleukin-6 receptor and genetic biomarkers BRCA1 and BRCA2, Phosphatase and tensin homolog, cellular myelocytomatosis oncogene and NKX3.1 may predict for aggressive high grade disease and are identifiable early in prostate carcinogenesis.

SUMMARY

One of the barriers of widespread adoption of active surveillance for low risk, localized prostate cancer is the concern that some patients may harbor occult high-risk disease at diagnosis, or develop more aggressive/noncurable disease not detected by our current well established prognostic factors. This review examines several serum and genetic-based biomarkers that appear to be of value in localized prostate cancer, unlike the vast majority of more established prostate cancer biomarkers that have been validated in far more advanced disease. Although the biomarkers discussed show exciting promise, their clinical utility is unknown, and their role in the active surveillance scenario needs further study.

Accuracy of multiparametric magnetic resonance imaging in confirming eligibility for active surveillance for men with prostate cancer

BACKGROUND

Active surveillance (AS) is an attempt to avoid overtreatment of clinically insignificant prostate cancer (PCa); however, patient selection remains controversial. Multiparametric prostate magnetic resonance imaging (MP-MRI) may help better select AS candidates.

METHODS

We reviewed a cohort of men who underwent MP-MRI with MRI/Ultrasound fusion-guided prostate biopsy and selected potential AS patients at entry using Johns Hopkins criteria. MP-MRI findings were assessed, including number of lesions, dominant lesion diameter, total lesion volume, prostate volume, and lesion density (calculated as total lesion volume/prostate volume). Lesions were assigned a suspicion score for cancer by MRI. AS criteria were reapplied based on the confirmatory biopsy, and accuracy of MP-MRI in predicting AS candidacy was assessed. Logistic regression modeling and chi-square statistics were used to assess associations between MP-MRI interpretation and biopsy results.

RESULTS

Eighty-five patients qualified for AS with a mean age of 60.2 years and mean prostate-specific antigen level of 4.8 ng/mL. Of these, 25 patients (29%) were reclassified as not meeting AS criteria based on confirmatory biopsy. Number of lesions, lesion density, and highest MRI lesion suspicion were significantly associated with confirmatory biopsy AS reclassification. These MRI-based factors were combined to create a nomogram that generates a probability for confirmed AS candidacy.

CONCLUSION

As clinicians counsel patients with PCa, MP-MRI may contribute to the decision-making process when considering AS. Three MRI-based factors (number of lesions, lesion suspicion, and lesion density) were associated with confirmatory biopsy outcome and reclassification. A nomogram using these factors has promising predictive accuracy for which future validation is necessary. Cancer 2013;119:3359-66. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Prostate cancer prevention: strategies for agent development

PURPOSE OF REVIEW

This article provides an update of clinical research supported by the National Cancer Institute's Phase I/II prostate cancer chemoprevention agent development program.

RECENT FINDINGS

Numerous clinical trials of pharmacologic interventions to delay, prevent or reverse carcinogenesis ('chemoprevention') with the ultimate goal of reducing cancer incidence have been conducted over the past decade. These trials range from relatively small, short-duration studies with biomarker endpoints to very large, long-term, general population trials with definitive cancer endpoints. Two large, population-based, Phase III prostate cancer prevention trials have shown a significant benefit for 5-α-reductase inhibitors. However, this class of agents was also associated with increased detection of high-grade prostate cancer. Another large, Phase III prostate cancer prevention trial showed no benefit for either selenium or vitamin E, given individually or in combination; in fact, a significant increase in prostate cancer was observed among men randomized to the vitamin E alone arm.

SUMMARY

A number of early phase trials and three definitive Phase III trials have been conducted in the field of prostate cancer prevention over the past decade. Although a great deal has been learned from these studies, significant work remains to be done to fully realize the potential of chemoprevention in this disease.

Eph receptors and their ligands: promising molecular biomarkers and therapeutic targets in prostate cancer

Although at present, there is a high incidence of prostate cancer, particularly in the Western world, mortality from this disease is declining and occurs primarily only from clinically significant late stage tumors with a poor prognosis. A major current focus of this field is the identification of new biomarkers which can detect earlier, and more effectively, clinically significant tumors from those deemed "low risk", as well as predict the prognostic course of a particular cancer. This strategy can in turn offer novel avenues for targeted therapies. The large family of Receptor Tyrosine Kinases, the Ephs, and their binding partners, the ephrins, has been implicated in many cancers of epithelial origin through stimulation of oncogenic transformation, tumor angiogenesis, and promotion of increased cell survival, invasion and migration. They also show promise as both biomarkers of diagnostic and prognostic value and as targeted therapies in cancer. This review will briefly discuss the complex roles and biological mechanisms of action of these receptors and ligands and, with regard to prostate cancer, highlight their potential as biomarkers for both diagnosis and prognosis, their application as imaging agents, and current approaches to assessing them as therapeutic targets. This review demonstrates the need for future studies into those particular family members that will prove helpful in understanding the biology and potential as targets for treatment of prostate cancer.