Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer

BACKGROUND

Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.

METHODS

All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.

RESULTS

Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.

CONCLUSIONS

We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

Nanomechanical-based classification of prostate tumor using atomic force microscopy

BACKGROUND

The loss of mechanical homeostasis between tumor cells and microenvironment is an important factor in tumor metastasis. In the process, mechanical forces affect cell proliferation, differentiation, migration and tissue development.

AIMS

Using high spatial resolution of Atomic force microscopy (AFM) technology, our study provides the direct measurement of the nanomechanical properties of prostate cancer clinical tissue specimens.

MATERIALS AND METHODS

AFM was used to determine the biomechanical properties of prostate tissue with different grade scores. K-means clustering method and fuzzy C-means were used to distinguish the cellular component in prostate tissue from non-cellular component based on their viscoelasticity. Futhermore, AFM measurements in vitro cells, including metastatic prostate cells (PC-3) and normal human prostate cells (PZ-HPV-7) were carried out.

RESULTS

The Young's modulus was decreased in prostate cancer progression, and the elasticity of cellular component in prostate cancer tissue was smaller than that of normal prostate tissue. PC-3 cells were softer than PZ-HPV-7 cells. Further mechanism investigation showed that the difference in modulus between cancerous and normal prostate tissue may be associated with a greater actin cytoskeleton distribution inside the cancer cells.

CONCLUSION

The results suggests that the nanomechanical properties can classify the prostate tumor, which could be used as an index for the identification and classification of cancer at cellular level.

Mutational spectrum of DNA damage and mismatch repair genes in prostate cancer

Over the past few years, a number of studies have revealed that a significant number of men with prostate cancer had genetic defects in the DNA damage repair gene response and mismatch repair genes. Certain of these modifications, notably gene alterations known as homologous recombination (HRR) genes; PALB2, CHEK2 BRCA1, BRCA2, ATM, and genes for DNA mismatch repair (MMR); MLH1, MSH2, MSH6, and PMS2 are connected to a higher risk of prostate cancer and more severe types of the disease. The DNA damage repair (DDR) is essential for constructing and diversifying the antigen receptor genes required for T and B cell development. But this DDR imbalance results in stress on DNA replication and transcription, accumulation of mutations, and even cell death, which compromises tissue homeostasis. Due to these impacts of DDR anomalies, tumor immunity may be impacted, which may encourage the growth of tumors, the release of inflammatory cytokines, and aberrant immune reactions. In a similar vein, people who have altered MMR gene may benefit greatly from immunotherapy. Therefore, for these treatments, mutational genetic testing is indicated. Mismatch repair gene (MMR) defects are also more prevalent than previously thought, especially in patients with metastatic disease, high Gleason scores, and diverse histologies. This review summarizes the current information on the mutation spectrum and clinical significance of DDR mechanisms, such as HRR and MMR abnormalities in prostate cancer, and explains how patient management is evolving as a result of this understanding.

Germline mutations in penetrant cancer predisposition genes are rare in men with prostate cancer selecting active surveillance

BACKGROUND

Pathogenic germline mutations in several rare penetrant cancer predisposition genes are associated with an increased risk of aggressive prostate cancer (PC). Our objectives were to determine the prevalence of pathogenic germline mutations in men with low-risk PC on active surveillance, and assess whether pathogenic germline mutations associate with grade reclassification or adverse pathology, recurrence, or metastases, in men treated after initial surveillance.

METHODS

Men prospectively enrolled in the Canary Prostate Active Surveillance Study (PASS) were retrospectively sampled for the study. Germline DNA was sequenced utilizing a hereditary cancer gene panel. Mutations were classified according to the American College of Clinical Genetics and Genomics' guidelines. The association of pathogenic germline mutations with grade reclassification and adverse characteristics was evaluated by weighted Cox proportional hazards modeling and conditional logistic regression, respectively.

RESULTS

Overall, 29 of 437 (6.6%) study participants harbored a pathogenic germline mutation of which 19 occurred in a gene involved in DNA repair (4.3%). Eight participants (1.8%) had pathogenic germline mutations in three genes associated with aggressive PC: ATM, BRCA1, and BRCA2. The presence of pathogenic germline mutations in DNA repair genes did not associate with adverse characteristics (univariate analysis HR = 0.87, 95% CI: 0.36-2.06, p = 0.7). The carrier rates of pathogenic germline mutations in ATM, BRCA1, and BRCA2did not differ in men with or without grade reclassification (1.9% vs. 1.8%).

CONCLUSION

The frequency of pathogenic germline mutations in penetrant cancer predisposition genes is extremely low in men with PC undergoing active surveillance and pathogenic germline mutations had no apparent association with grade reclassification or adverse characteristics.

Prognostic Genomic Tissue-Based Biomarkers in the Treatment of Localized Prostate Cancer

In localized prostate cancer clinicopathologic variables have been used to develop prognostic nomograms quantifying the probability of locally advanced disease, of pelvic lymph node and distant metastasis at diagnosis or the probability of recurrence after radical treatment of the primary tumor. These tools although essential in daily clinical practice for the management of such a heterogeneous disease, which can be cured with a wide spectrum of treatment strategies (i.e., active surveillance, RP and radiation therapy), do not allow the precise distinction of an indolent instead of an aggressive disease. In recent years, several prognostic biomarkers have been tested, combined with the currently available clinicopathologic prognostic tools, in order to improve the decision-making process. In the following article, we reviewed the literature of the last 10 years and gave an overview report on commercially available tissue-based biomarkers and more specifically on mRNA-based gene expression classifiers. To date, these genomic tests have been widely investigated, demonstrating rigorous quality criteria including reproducibility, linearity, analytical accuracy, precision, and a positive impact in the clinical decision-making process. Albeit data published in literature, the systematic use of these tests in prostate cancer is currently not recommended due to insufficient evidence.

Outcomes of active surveillance for clinically localized prostate cancer in a middle eastern tertiary care center

BACKGROUND

The aim of our study was to evaluate the outcome of active surveillance (AS) for prostate cancer for a cohort of patients at our institution.

METHODS

A total of 43 patients with low risk prostate cancer were enrolled in an active surveillance pilot program at our institution between 2008 and 2018. Follow up protocols included: periodic prostate specific antigen (PSA), digital rectal examination (DRE), multiparametric MRI, and prostate biopsy at one year. Pertinent parameters were collected, and descriptive statistics were reported along with a subset analysis of patients that dropped out of the protocol to receive active treatment for disease progression.

RESULTS

Out of 43 eligible patients, 46.5% had a significant rise in follow up PSA. DRE was initially suspicious in 27.9% of patients, and none had any change in DRE on follow up. Initially, prostate MRIs showed PIRADS 3, 4, and 5 in 14%, 37.2%, and 11.6% respectively, while 23.2% had a negative initial MRI. 14% did not have an MRI. Upon follow up, 18.6% of patients had progression on MRI. Initial biopsies revealed that 86% were classified as WHO group 1, while 14% as WHO group 2. With regards to the follow up biopsies, 11.6% were upgraded. 20.9% of our patients had active treatment; 44.4% due to upgraded biopsy results, 22.2% due to PSA progression, 22.2% due to strong patient preference, and 11.1% due to radiologic progression.

CONCLUSIONS

For selected men with low risk prostate cancer, AS is a reasonable alternative. The decision for active treatment should be tailored upon changes in PSA, DRE, MRI, and biopsy results.

miR-145-5p: A Potential Biomarker in Predicting Gleason Upgrading of Prostate Biopsy Samples Scored 3+3=6

Background

The Gleason grading system is a major tool used for prediction of prostate cancer (PCa) behavior. Because of heterogeneity and sampling errors, prognosis is variable even among patients with the same Gleason score (GS). Therefore, more accurate biomarkers that complement the Gleason system are needed to improve the clinical management of PCa.

Methods

Formalin-fixed, paraffin embedded tissue samples were obtained from radical prostatectomy (RP) (patient set 1, n=53) and needle biopsy (patient set 2, n=107; patient set 3, n=119). Cancer tissues from pure regions of each Gleason pattern (GP) were separately collected using laser-captured microdissection, followed by Real-time-PCR to determine the relative expression of miRNAs, including miR-1-5p, miR-21-5p, miR-30d-5p, miR-100-5p, miR-145-5p, miR-224-5p, and miR-708-5p. miRNA’s association with Gleason upgrading (GU) was evaluated using receiver operator characteristics (ROC) curve and multivariate logistic regression analysis. The integrated miRNA targets prediction and enrichment analyses were performed to determine the potential functions of miRNA.

Results

It was found that miR-145-5p in GP3 from radical prostatectomy (RP) were overexpressed in patients with GS6 PCa compared with GS7 patients, which was further confirmed in a larger biopsy cohort. ROC curve analysis revealed that miR-145-5p in biopsy was significantly associated with GU upon RP. In multivariate analyses, miR-145-5p was an independent predictor of GU.

Conclusion

Our study indicated that differential expression of miRNAs existed in GP3 from pure GS6 and GS7 PCa, highlighting a path toward the clinical use of miRNAs in predicting GU and assisting in treatment modality selection.

High DND1 Level Indicates a Poor Prognostic Factor in Prostate Cancer

Background

Dead end 1 (DND1) plays a vital role during oncogenesis and cancer progression by regulating the mRNA content via competitive combination with miRNA, but what function it exerts in prostate cancer has been unclear. The purpose of this paper is to explore the correlation between DND1 expression levels and clinical characteristics in prostate cancer (PCa) patients.

Materials and Methods

To assess the expression of DND1 in tumor specimens compared with paired paracancerous tissues, the sample from 83 patients was analyzed by immunohistochemistry. The Cancer Genome Atlas (TCGA) database was used to verify our results. Subsequently, we statistically analyzed the relationship between DND1 expression and the clinical prognosis of PCa patients.

Results

Compared with paracancerous tissues, DND1 has a higher expression level in prostate cancer. The overexpression of DND1 in protein level was significantly associated with the higher clinical stage (P = 0.006), ISUP grading group (P < 0.001), seminal vesicle invasion (P = 0.006), and PSA density (P = 0.002). Furthermore, the overexpression of DND1 indicates a poor clinical prognosis in prostate cancer patients.

Conclusion

High-level expression of DND1 was associated with tumor progression and poor clinical prognosis. Hence, DND1 may become a potential prognostic biomarker for PCa.

A first step towards a global nomogram to predict disease progression for men on active surveillance

BACKGROUND

Signs of disease progression (28%) and conversion to active treatment without evidence of disease progression (13%) are the main reasons for discontinuation of active surveillance (AS) in men with localised prostate cancer (PCa). We aimed to develop a nomogram to predict disease progression in these patients.

METHODS

As a first step in the development of a nomogram, using data from Movembers' GAP3 Consortium (n=14,380), we assessed heterogeneity between centres in terms of risk of disease progression. We started with assessment of baseline hazards for disease progression based on grouping of centres according to follow-up protocols [high: yearly; intermediate: ~2 yearly; and low: at year 1, 4 & 7 (i.e., PRIAS)]. We conducted cause-specific random effect Cox proportional hazards regression to estimate risk of disease progression by centre in each group.

RESULTS

Disease progression rates varied substantially between centres [median hazard ratio (MHR): 2.5]. After adjustment for various clinical factors (age, year of diagnosis, Gleason grade group, number of positive cores and PSA), substantial heterogeneity in disease progression remained between centres.

CONCLUSIONS

When combining worldwide data on AS, we noted unexplained differences of disease progression rate even after adjustment for various clinical factors. This suggests that when developing a global nomogram, local adjustments for differences in risk of disease progression and competing outcomes such as conversion to active treatment need to be considered.

Tailoring Intensity of Active Surveillance for Low-Risk Prostate Cancer Based on Individualized Prediction of Risk Stability

Importance

Active surveillance is increasingly recognized as the preferred standard of care for men with low-risk prostate cancer. However, active surveillance requires repeated assessments, including prostate-specific antigen tests and biopsies that may increase anxiety, risk of complications, and cost.

Objective

To identify and validate clinical parameters that can identify men who can safely defer follow-up prostate cancer assessments.

Design, Setting, and Participants

The Canary Prostate Active Surveillance Study (PASS) is a multicenter, prospective active surveillance cohort study initiated in July 2008, with ongoing accrual and a median follow-up period of 4.1 years. Men with prostate cancer managed with active surveillance from 9 North American academic medical centers were enrolled. Blood tests and biopsies were conducted on a defined schedule for least 5 years after enrollment. Model validation was performed among men at the University of California, San Francisco (UCSF) who did not enroll in PASS. Men with Gleason grade group 1 prostate cancer diagnosed since 2003 and enrolled in PASS before 2017 with at least 1 confirmatory biopsy after diagnosis were included. A total of 850 men met these criteria and had adequate follow-up. For the UCSF validation study, 533 active surveillance patients meeting the same criteria were identified. Exclusion criteria were treatment within 6 months of diagnosis, diagnosis before 2003, Gleason grade score of at least 2 at diagnosis or first surveillance biopsy, no surveillance biopsy, or missing data.

Exposures

Active surveillance for prostate cancer.

Main Outcomes and Measures

Time from confirmatory biopsy to reclassification, defined as Gleason grade group 2 or higher on subsequent biopsy.

Results

A total of 850 men (median [interquartile range] age, 64 [58-68] years; 774 [91%] White) were included in the PASS cohort. A total of 533 men (median [interquartile range] age, 61 [57-65] years; 422 [79%] White) were included in the UCSF cohort. Parameters predictive of reclassification on multivariable analysis included maximum percent positive cores (hazard ratio [HR], 1.30 [95% CI, 1.09-1.56]; P = .004), history of any negative biopsy after diagnosis (1 vs 0: HR, 0.52 [95% CI, 0.38-0.71]; P < .001 and ≥2 vs 0: HR, 0.18 [95% CI, 0.08-0.4]; P < .001), time since diagnosis (HR, 1.62 [95% CI, 1.28-2.05]; P < .001), body mass index (HR, 1.08 [95% CI, 1.05-1.12]; P < .001), prostate size (HR, 0.40 [95% CI, 0.25-0.62]; P < .001), prostate-specific antigen at diagnosis (HR, 1.51 [95% CI, 1.15-1.98]; P = .003), and prostate-specific antigen kinetics (HR, 1.46 [95% CI, 1.23-1.73]; P < .001). For prediction of nonreclassification at 4 years, the area under the receiver operating curve was 0.70 for the PASS cohort and 0.70 for the UCSF validation cohort. This model achieved a negative predictive value of 0.88 (95% CI, 0.83-0.94) for those in the bottom 25th percentile of risk and of 0.95 (95% CI, 0.89-1.00) for those in the bottom 10th percentile.

Conclusions and Relevance

In this study, among men with low-risk prostate cancer, heterogeneity prevailed in risk of subsequent disease reclassification. These findings suggest that active surveillance intensity can be modulated based on an individual's risk parameters and that many men may be safely monitored with a substantially less intensive surveillance regimen.

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance

In this work, we assessed the ability of computerized features of nuclear morphology from diagnostic biopsy images to predict prostate cancer (CaP) progression in active surveillance (AS) patients. Improved risk characterization of AS patients could reduce over-testing of low-risk patients while directing high-risk patients to therapy. A total of 191 (125 progressors, 66 non-progressors) AS patients from a single site were identified using The Johns Hopkins University's (JHU) AS-eligibility criteria. Progression was determined by pathologists at JHU. 30 progressors and 30 non-progressors were randomly selected to create the training cohort D₁ (n = 60). The remaining patients comprised the validation cohort D₂ (n = 131). Digitized Hematoxylin & Eosin (H&E) biopsies were annotated by a pathologist for CaP regions. Nuclei within the cancer regions were segmented using a watershed method and 216 nuclear features describing position, shape, orientation, and clustering were extracted. Six features associated with disease progression were identified using D₁ and then used to train a machine learning classifier. The classifier was validated on D₂. The classifier was further compared on a subset of D₂ (n = 47) against pro-PSA, an isoform of prostate specific antigen (PSA) more linked with CaP, in predicting progression. Performance was evaluated with area under the curve (AUC). A combination of nuclear spatial arrangement, shape, and disorder features were associated with progression. The classifier using these features yielded an AUC of 0.75 in D₂. On the 47 patient subset with pro-PSA measurements, the classifier yielded an AUC of 0.79 compared to an AUC of 0.42 for pro-PSA. Nuclear morphometric features from digitized H&E biopsies predicted progression in AS patients. This may be useful for identifying AS-eligible patients who could benefit from immediate curative therapy. However, additional multi-site validation is needed.

Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer

In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient's prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the disease and provide an enhanced assessment of prognosis. Herein, we review novel prognostic biomarkers and their integration into risk assessment models for prostate cancer focusing on their capability to help avoid unnecessary imaging studies, biopsies and diagnosis of low risk prostate cancers, to help in the decision-making process between active surveillance and treatment intervention, and to predict recurrence after radical prostatectomy. There is an imperative need of reliable biomarkers to stratify prostate cancer patients that may benefit from different management approaches. The integration of biomarkers panel with risk assessment models appears to improve prostate cancer diagnosis and management. However, integration of novel genomic biomarkers in future prognostic models requires further validation in their clinical efficacy, standardization, and cost-effectiveness in routine application.

A novel nomogram to identify candidates for active surveillance amongst patients with International Society of Urological Pathology (ISUP) Grade Group (GG) 1 or ISUP GG2 prostate cancer, according to multiparametric magnetic resonance imaging findings

OBJECTIVES

To develop a novel nomogram to identify candidates for active surveillance (AS) that combines clinical, biopsy and multiparametric magnetic resonance imaging (mpMRI) findings; and to compare its predictive accuracy to, respectively: (i) Prostate Cancer Research International: Active Surveillance (PRIAS) criteria, (ii) Johns Hopkins (JH) criteria, (iii) European Association of Urology (EAU) low-risk classification, and (iv) EAU low-risk or low-volume with International Society of Urological Pathology (ISUP) Grade Group (GG) 2 classification.

PATIENTS AND METHODS

We selected 1837 patients with ISUP GG1 or GG2 prostate cancer (PCa), treated with radical prostatectomy (RP) between 2012 and 2018. The outcome of interest was the presence of unfavourable disease (i.e., clinically significant PCa [csPCa]) at RP, defined as: ISUP GG ≥ 3 and/or pathological T stage (pT) ≥3a and/or pathological N stage (pN) 1. First, logistic regression models including PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 binary classifications (not eligible vs eligible) were used. Second, a multivariable logistic regression model including age, prostate-specific antigen density (PSA-D), ISUP GG, and the percentage of positive cores (Model 1) was fitted. Third, Prostate Imaging-Reporting and Data System (PI-RADS) score (Model 2), extracapsular extension (ECE) score (Model 3) and PI-RADS + ECE score (Model 4) were added to Model 1. Only variables associated with higher csPCa rates in Model 4 were retained in the final simplified Model 5. The area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analyses were used.

RESULTS

Of the 1837 patients, 775 (42.2%) had csPCa at RP. Overall, 837 (47.5%), 986 (53.7%), 348 (18.9%), and 209 (11.4%) patients were eligible for AS according to, respectively, the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS, and JH criteria. The proportion of csPCa amongst the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS and JH candidates was, respectively 28.5%, 29.3%, 25.6% and 17.2%. Model 4 and Model 5 (in which only PSA-D, ISUP GG, PI-RADS and ECE score were retained) had a greater AUC (0.84), compared to the four proposed AS criteria (all P < 0.001). The adoption of a 25% nomogram threshold increased the proportion of AS-eligible patients from 18.9% (PRIAS) and 11.4% (JH) to 44.4%. Moreover, the same 25% nomogram threshold resulted in significantly lower estimated risks of csPCa (11.3%), compared to PRIAS (Δ: -14.3%), JH (Δ: -5.9%), EAU low-risk (Δ: -17.2%), and EAU low-risk or low-volume ISUP GG2 classifications (Δ: -18.0%).

CONCLUSION

The novel nomogram combining clinical, biopsy and mpMRI findings was able to increase by ~25% and 35% the absolute frequency of patients suitable for AS, compared to, respectively, the PRIAS or JH criteria. Moreover, this nomogram significantly reduced the estimated frequency of csPCa that would be recommended for AS compared to, respectively, the PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 classifications.

Establishment and Validation of Extra-transitional Zone Prostate Specific Antigen Density (ETzD), a Novel Structure-based Parameter for Quantifying the Oncological Hazard of Prostates with Enlarged Stroma

Extra-transitional zone density (ETzD), a novel parameter is proposed to stratify the deviation of prostate specific antigen (PSA) due to structural change according to stromal hyperplasia of prostate. ETzD was conducted on a concept to estimate the PSA density (PSAD) after hypothetical enucleation of the transitional zone of an enlarged prostate by a non-linear regression prediction model with intrinsic linearity, from the retrospective analysis of PSA change observed actual enucleation by laser. The performance to predict the presence and severity of malignancy was validated by two cohorts of 3,440 prostate biopsies and 2,783 radical prostatectomy specimens. The performance of ETzD was compared with conventional parameters. The receiver operative curve of area under curve (AUC) of ETzD to predict the presence of malignacy was 0.862 (95% CI; 0.843~0.881), better than PSA, PSAD or transitional zone PSAD (TzPSAD). The AUC of ETzD to predict an unfavorable cancer among prostate cancer patients was 0.736 (95% CI; 0.705~0.768), which performs better than PSA and comparable to PSAD or TzPSAD. In summary, the performance of ETzD as a universal parameter to quantify the oncological hazard of a prostate was validated and the superiority to conventional parameters was verified.

Prostate Biopsy in Active Surveillance Protocols: Immediate Re-biopsy and Timing of Subsequent Biopsies

PURPOSE OF REVIEW

This manuscript reviews contemporary literature regarding prostate cancer active surveillance (AS) protocols as well as other tools that may guide the management of biopsy frequency and assess the possibility of progression in low-risk prostate cancer.

RECENT FINDINGS

There is no consensus regarding the timing of surveillance biopsies; however, an immediate repeat biopsy within 12 months of diagnosis for patients considering AS confirms patients who have favorable risk disease yet also identifies patients who were undersampled initially. Studies regarding multiparametric MRI, nomograms, and biomarkers show promise in risk stratifying and counseling patients during AS. Further studies are needed to determine if these supplemental tests can decrease the frequency of surveillance biopsies. An immediate re-biopsy can help to reduce the risk of missing clinically significant disease. Other clinical tools, including mpMRI, exist that can be used as an adjunct to counsel patients and guide a personalized discussion regarding the frequency of surveillance biopsies.

Biomarkers in prostate cancer - Current clinical utility and future perspectives

Current tendencies in the treatment course of prostate cancer patients increase the need for reliable biomarkers that help in decision-making in a challenging clinical setting. Within the last decade, several novel biomarkers have been introduced. In the following comprehensive review article, we focus on diagnostic (PHI^®, 4K score, SelectMDx^®, ConfirmMDx^®, PCA3, MiPS, ExoDX^®, mpMRI) and prognostic (OncotypeDX GPS^®, Prolaris^®, ProMark^®, DNA-ploidy, Decipher^®) biomarkers that are in widespread clinical use and are supported by evidence. Hereby, we focus on multiple clinical situations in which innovative biomarkers may guide decision-making in prostate cancer therapy. In addition, we describe novel liquid biopsy approaches (circulating tumor cells, cell-free DNA) that have been described as predictive biomarkers in metastatic castration-resistant prostate cancer and might support an individual patient-centred oncological approach in the nearer future.

Development of a new nomogram to predict insignificant prostate cancer in patients undergoing radical prostatectomy

OBJECTIVE

The aim of this study was to develop a nomogram to predict the probability of insignificant prostate cancer.

MATERIALS AND METHODS

A retrospective analysis was conducted of patients who underwent radical prostatectomy at a Korean hospital between January 2005 and December 2014. Patients with pathologically insignificant prostate cancer were defined as having organ-confined disease with tumor volume less than 0.5 cm³ without Gleason scores of 4 or 5. Multivariable logistic regression analysis with a stepwise selection was used to model the relationship between preoperative characteristics and insignificant prostate cancer, and a nomogram to predict the probability of insignificant prostate cancer was created. Receiver operating characteristics (ROC) analysis was performed to assess the predictive value of the model.

RESULTS

The final study population consisted of 1343 patients. Among these patients, insignificant prostate cancer was confirmed in 188 men (14.0%) at the time of prostatectomy. Six independent predictors of insignificant prostate cancer were identified: number of positive cores (p < 0.001), maximal single core tumor involvement (p < 0.001), biopsy Gleason score (p < 0.001), prostate volume (p = 0.024), patient age (p < 0.001) and prostate-specific antigen density (p < 0.001) in the multivariable model. A nomogram to predict insignificant prostate cancer was developed using these six preoperative characteristics. The area under the ROC curve for nomogram predictions was 0.87.

CONCLUSION

The nomogram developed in this paper identifies the probability of insignificant prostate cancer and gives providers more information to guide their clinical decisions.

Risk Stratification of Newly Diagnosed Prostate Cancer with Genomic Platforms

INTRODUCTION

Interest in novel risk stratification tools for men with newly diagnosed prostate cancer has flourished, aiming to offer increasingly accurate predictions of future disease behavior to ultimately better guide clinical management. We highlight the use of genomic platforms attempting to refine clinical decisions at the point of initial diagnosis.

METHODS

In the context of a benchmark standard of clinical risk stratification tools we reviewed the role of genomic tests, including individual gene expression assays, as well as a growing number of tissue based expression tests assessing multiple gene panels, to improve predictions at initial diagnosis.

RESULTS

The role of single gene status including TMPRSS2:ERG fusion and PTEN expression has been investigated among men with newly diagnosed prostate cancer. Gene expression profiles incorporating panels of genes associated with prostate cancer outcome have received external validation and have commercial application in assays that incorporate baseline clinical risk to offer predictions of immediate pathological and downstream disease end points. Comparisons of gene signatures have offered insights into relative predictive performance in archival tissue. However, to date no studies appear to directly support a single genomic assay offering superior clinical usefulness for decision making at the time of diagnosis.

CONCLUSIONS

Risk stratification tools incorporating genomic analysis of prostate cancer have been developed which seek to improve the accuracy of initial predictions. Further study is warranted to define the additive clinical benefit associated with their use if implemented broadly.

Clinical Utility of Biomarkers in Localized Prostate Cancer

A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emerging tests, with attention on studies addressing clinical utility.

Predictive models and risk of biopsy progression in active surveillance patients

OBJECTIVE

To analyze the performance of different radical prostatectomy-based prognostic tools in predicting the biopsy progression in our active surveillance cohort.

MATERIALS AND METHODS

We analyzed 326 patients with biopsy Gleason grade≤6,≤2 positive biopsy cores,≤20% tumor present in any core, prostate-specific antigen<15ng/dl, and clinical stages T1-T2a all of whom had at least single surveillance biopsy. Probabilities of pathologically relatively aggressive disease were estimated using Partin and Dinh risk tables and Kattan, Truong, and Kulkarni nomograms for each individual patient. Using these predictions, performance of these tools was quantified regarding discrimination, stratification at different cut-points, calibration, and the clinical net benefit.

RESULTS

Predictions of Partin and Dinh tables were not associated with the biopsy progression. The predictive value of Kattan and Truong nomograms was higher when compared with the other tools, although it was significant only on the first and second surveillance biopsies. Both nomograms were able to identify low- and high-risk subgroups within the cohort. Kattan nomogram demonstrated better correlation with the observed rate of progression over the first 3 biopsies and higher clinical net benefit.

CONCLUSION

Kattan and Truong nomograms demonstrated the best performance in predicting biopsy progression, although their value was largely limited to the first 2 surveillance biopsies. Both tools were able to stratify patients into subgroups with different risks of progression. These nomograms have important differences, which suggest that a more effective predictive model combining the strong sides of both tools and possibly some other variables could be developed.

A biopsy-integrated algorithm for determining Gleason 6 upgrading risk stratifies risk of active surveillance failure in prostate cancer

INTRODUCTION

A significant proportion of patients that fail active surveillance (AS) for prostate cancer management do so because of cancer upgrading. A previously validated upgrading nomogram generates a score that predicts risk of biopsy Gleason 6 upgrading following radical prostatectomy in lower-risk populations that are candidates for Active Surveillance (Cancer, 2013).

OBJECTIVES

We hypothesize that the upgrading risk (UR) score generated by this nomogram at diagnosis improves the ability to predict patients that will subsequently fail AS.

METHODS

To evaluate the nomogram, retrospective data from several institutional cohorts of patients who met AS criteria, group 1 (n = 75) and group 2 (n = 1230), were independently examined. A UR score was generated using the coefficients from the nomogram consisting of PSA density (PSAD), BMI, maximum % core involvement (MCI), and number of positive cores. AS failure was defined as Gleason score (GS) >6, >50 % maximum core involvement, or >2 positive cores on biopsy. Univariate and multivariate Cox proportional-hazards regression models, upgrading risk score, and other clinicopathologic features were each assessed for their ability to predict AS failure.

RESULTS

Clinicopathologic parameters were similar in both groups with the exception of mean PSAD (0.13 vs. 0.11, p < 0.01) and follow-up (2.1 vs. 3.2 years, p = 0.2). Most common cause of AS failure was GS > 6 (group 1) compared to >2 positive cores (group 2). On univariate analysis in both populations, features at diagnosis including PSAD and the UR score were significant in predicting AS failure by upgrading (Gleason > 6) and any failure. Multivariate analysis revealed the UR score predicts AS failure by GS upgrading (HR 1.8, 95 % CI 1.12-2.93; p = 0.01) and any failure criteria (HR 1.7, 95 % CI 1.06-2.65); p = 0.02) for group 1. Likewise, the UR score in group 2 predicts AS failure with GS upgrading (HR 1.3, 95 % CI 1.15-1.42; p < 0.0001) and any failure criteria (HR 1.18, 95 % CI 1.18-1.38; p < 0.0001). An ROC generated an AUC of 0.66. Decision curve analysis demonstrated a high net benefit for the UR score across a range of threshold probabilities. Based on these outcomes, at 3 years, patients in the lowest risk quartile have a 15 % risk of AS failure versus a 46 % risk in the highest quartile (p < 0.0001).

CONCLUSIONS

The UR score was predictive of pathologic AS failure on multivariate analysis in several AS cohorts. It outperformed single clinicopathologic criteria and may provide a useful adjunct using clinicopathologic data to stratify patients considering AS.

KI67 and DLX2 predict increased risk of metastasis formation in prostate cancer-a targeted molecular approach

Background:

There remains a need to identify and validate biomarkers for predicting prostate cancer (CaP) outcomes using robust and routinely available pathology techniques to identify men at most risk of premature death due to prostate cancer. Previous immunohistochemical studies suggest the proliferation marker Ki67 might be a predictor of survival, independently of PSA and Gleason score. We performed a validation study of Ki67 as a marker of survival and disease progression and compared its performance against another candidate biomarker, DLX2, selected using artificial neural network analysis.

Methods:

A tissue microarray (TMA) was constructed from transurethral resected prostatectomy histology samples (n=192). Artificial neural network analysis was used to identify candidate markers conferring increased risk of death and metastasis in a public cDNA array. Immunohistochemical analysis of the TMA was carried out and univariate and multivariate tests performed to explore the association of tumour protein levels of Ki67 and DLX2 with time to death and metastasis.

Results:

Univariate analysis demonstrated Ki67 as predictive of CaP-specific survival (DSS; P=0.022), and both Ki67 (P=0.025) and DLX2 (P=0.001) as predictive of future metastases. Multivariate analysis demonstrated Ki67 as independent of PSA, Gleason score and D'Amico risk category for DSS (HR=2.436, P=0.029) and both Ki67 (HR=3.296, P=0.023) and DLX2 (HR=3.051, P=0.003) as independent for future metastases.

Conclusions:

High Ki67 expression is only present in 6.8% of CaP patients and is predictive of reduced survival and increased risk of metastasis, independent of PSA, Gleason score and D'Amico risk category. DLX2 is a novel marker of increased metastasis risk found in 73% patients and 8.2% showed co-expression with a high Ki67 score. Two cancer cell proliferation markers, Ki67 and DLX2, may be able to inform clinical decision-making when identifying patients for active surveillance.

Confirmatory biopsy for the assessment of prostate cancer in men considering active surveillance: reference centre experience

OBJECTIVES

To evaluate how accurate a 12-core transrectal biopsy derived low-risk prostate cancer diagnosis is for an active surveillance programme by comparing the histological outcome with that from confirmatory transperineal sector biopsy.

SUBJECTS AND METHODS

The cohort included 166 men diagnosed with low volume Gleason score 3+3 prostate cancer on initial transrectal biopsy who also underwent a confirmatory biopsy. Both biopsy techniques were performed according to standard protocols and samples were taken for histopathology analysis. Subgroup analysis was performed according to disease severity at baseline to determine possible disease parameters of upgrading at confirmatory biopsy.

RESULTS

After confirmatory biopsy, 34% demonstrated Gleason score upgrade, out of which 25% were Gleason score 3+4 and 8.5% primary Gleason pattern 4. Results remained consistent for the subgroup analysis and a weak positive association, but not statistically significant, between prostate specific antigen (PSA), age, and percentage of positive cores, and PCa upgrading at confirmatory biopsy was found.

CONCLUSION

In our single centre study, we found that one-third of patients had higher Gleason score at confirmatory biopsy. Furthermore 8.5% of these upgraders had a primary Gleason pattern 4. Our results together with previously published evidence highlight the need for the revision of current guidelines in prostate cancer diagnosis for the selection of men for active surveillance.

Patient and disease factors affecting the choice and adherence to active surveillance

PURPOSE OF REVIEW

Treatment decisions for low-risk prostate cancer are arguably some of the most challenging in oncology. Active surveillance has emerged as an important option for many men with tumors estimated to have a low metastatic potential. Multiple complex patient and physician factors affect the recommendation, selection, and adherence to active surveillance. While baseline clinical criteria are used to identify candidates for this approach, it is important to identify and understand other forces that may influence the management of prostate cancer with active surveillance.

RECENT FINDINGS

Patient perceptions and acceptance of active surveillance have improved over time. Treatment decisions for prostate cancer are strongly associated with physician recommendations, and a high-quality relationship between the patient and his healthcare system is critical to successful active surveillance. Patient understanding of prostate cancer and consistency of information received from separate physicians can affect a decision to pursue active surveillance. Psychological symptoms, most notably regarding anxiety and distress, can affect adherence to active surveillance over time. In general, anxiety for men on active surveillance is low, and lifestyle interventions and self-management strategies may be helpful for increasing quality of life and limiting abandonment of active surveillance in the absence of disease progression.

SUMMARY

Multiple factors may affect the decision for and adherence to active surveillance for prostate cancer. It is important for both physicians and patients to be aware of these issues and work towards individualized approaches and interventions as needed to increase adoption of active surveillance in the future.

Identification of candidates for observation

PURPOSE OF REVIEW

The clinical value of active surveillance may still be limited due to acceptance and considerable misclassification rates, and inadequate follow-up criteria. This review focuses on the most recent developments in the use of active surveillance and patient-specific factors that may be used to identify patients suitable for this strategy.

RECENT FINDINGS

The number of patients diagnosed with low-risk prostate cancer has risen. Active surveillance acceptance rates are increasing, but still limited and varying importantly (2-49%). Misclassification is inevitable in all currently used protocols, although most of these patients still have relatively favorable-risk prostate cancer. African-American race, obese, and older-aged patients show more unfavorable intermediate results in an active surveillance situation. These are unlikely to be explained by the small differences in preoperative characteristics only. Psychological profiling may also be added to the selection process. Most studies report intermediate endpoints only.

SUMMARY

Patient-specific factors may be incorporated when identifying patients for active surveillance. This does not imply that active surveillance is not justified in specific groups, but may suggest the need for an intensified and personalized selection, instead of a one-size-fits-all approach.

[Active surveillance for low-risk prostate cancer]

Autopsy studies have confirmed the high prevalence of latent prostate cancer; however, only a certain portion of patients require definite treatment. Active surveillance is one of the treatment options which, according to national and international guidelines, should be offered to patients with newly diagnosed low-risk prostate cancer. Prostate cancer-specific survival is high in these patients; therefore, curative treatment, such as radical prostatectomy, external beam radiotherapy and brachytherapy may be initially deferred in order to avoid therapy-related side effects. In order to qualify for active surveillance, strict inclusion criteria have to be met; nevertheless, the reliable identification of low-risk prostate cancer patients is not always possible. Patients under active surveillance are followed up regularly with prostate-specific antigen (PSA) testing, digital rectal examination (DRE) and repeat prostate biopsies. Due to the heterogeneity of primary prostate tumors precise molecular diagnostic techniques could allow individualized treatment strategies in the future.

Can Confirmatory Biopsy be Omitted in Patients with Prostate Cancer Favorable Diagnostic Features on Active Surveillance?

PURPOSE

We evaluated whether initial diagnostic parameters could predict the confirmatory biopsy result in patients initiating active surveillance for prostate cancer, to determine whether some men at low risk for disease reclassification could be spared unnecessary biopsy.

MATERIALS AND METHODS

The cohort included 392 men with Gleason 6 prostate cancer on initial biopsy undergoing confirmatory biopsy. We used univariate and multivariable logistic regression to assess if high grade cancer (Gleason 7 or greater) on confirmatory biopsy could be predicted from initial diagnostic parameters (prostate specific antigen density, magnetic resonance imaging result, percent positive cores, percent cancer in positive cores and total tumor length).

RESULTS

Median patient age was 62 years (IQR 56-66) and 47% of patients had a dominant or focal lesion on magnetic resonance imaging. Of the 392 patients 44 (11%) had high grade cancer on confirmatory biopsy, of whom 39 had Gleason 3+4, 1 had 4+3, 3 had Gleason 8 and 1 had Gleason 9 disease. All predictors were significantly associated with high grade cancer at confirmatory biopsy on univariate analysis. However, in the multivariable model only prostate specific antigen density and total tumor length were significantly associated (AUC 0.85). Using this model to select patients for confirmatory biopsy would generally provide a higher net benefit than performing confirmatory biopsy in all patients, across a wide range of threshold probabilities.

CONCLUSIONS

If externally validated, a model based on initial diagnostic criteria could be used to avoid confirmatory biopsy in many patients initiating active surveillance.

Active surveillance for prostate cancer: when to recommend delayed intervention

There are no agreed upon guidelines for placing patients on active surveillance (AS). Therefore, there are no absolute criteria for taking patients off AS and when to recommend treatment. The criteria used to define progression are currently based on prostate specific antigen (PSA) kinetics, biopsy reclassification, and change in clinical stage. Multiple studies have evaluated predictors of progression such as PSA, PSA density (PSAD), prostate volume, core positivity, and visible lesion on multiparametric magnetic resonance imaging (mpMRI). Furthermore, published nomograms designed to predict indolent prostate cancer do not perform well when used to predict progression. Newer biomarkers have also not performed well to predict progression. These findings highlight that clinical and pathologic variables are not enough to identify patients that will progress while on AS. In the future, with the use of imaging, biomarkers, and gene expression assays, we should be better equipped to diagnose/stage prostate cancer and to distinguish between insignificant and significant disease.

Rule-based versus probabilistic selection for active surveillance using three definitions of insignificant prostate cancer

PURPOSE

To study whether probabilistic selection by the use of a nomogram could improve patient selection for active surveillance (AS) compared to the various sets of rule-based AS inclusion criteria currently used.

METHODS

We studied Dutch and Swedish patients participating in the European Randomized study of Screening for Prostate Cancer (ERSPC). We explored which men who were initially diagnosed with cT1-2, Gleason 6 (Gleason pattern ≤3 + 3) had histopathological indolent PCa at RP [defined as pT2, Gleason pattern ≤3 and tumour volume (TV) ≤0.5 or TV ≤ 1.3 ml, and TV no part of criteria (NoTV)]. Rule-based selection was according to the Prostate cancer Research International: Active Surveillance (PRIAS), Klotz, and Johns Hopkins criteria. An existing nomogram to define probability-based selection for AS was refitted for the TV1.3 and NoTV indolent PCa definitions.

RESULTS

619 of 864 men undergoing RP had cT1-2, Gleason 6 disease at diagnosis and were analysed. Median follow-up was 8.9 years. 229 (37%), 356 (58%), and 410 (66%) fulfilled the TV0.5, TV1.3, and NoTV indolent PCa criteria at RP. Discriminating between indolent and significant disease according to area under the curve (AUC) was: TV0.5: 0.658 (PRIAS), 0.523 (Klotz), 0.642 (Hopkins), 0.685 (nomogram). TV1.3: 0.630 (PRIAS), 0.550 (Klotz), 0.615 (Hopkins), 0.646 (nomogram). NoTV: 0.603 (PRIAS), 0.530 (Klotz), 0.589 (Hopkins), 0.608 (nomogram).

CONCLUSIONS

The performance of a nomogram, the Johns Hopkins, and PRIAS rule-based criteria are comparable. Because the nomogram allows individual trade-offs, it could be a good alternative to rigid rule-based criteria.

A urine-based methylation signature for risk stratification within low-risk prostate cancer

Background:

Prostate cancer overdiagnosis and overtreatment represents a major problem. Many men with low-grade disease on biopsy are undergraded and they harbour high-grade disease at prostatectomy with no reliable way to identify these men. We used a novel urine-based 2-gene methylation test to identify prostate cancers with aggressive features.

Methods:

Following a proof of concept study in 100 post-radical prostatectomy tissue samples, urine samples were tested from 665 men at multiple U.S. centers undergoing prostate needle biopsy for elevated prostate-specific antigen (2–10 ng ml⁻¹). A prediction model was then developed from a combination of clinical factors and the urine-based markers. It was then prospectively tested for accurate prediction of adverse disease (surgical Gleason score ⩾7 and/or a pathological stage ⩾T3a) using urine from a separate cohort of 96 men before radical prostatectomy.

Results:

Among pre-prostatectomy men with a biopsy Gleason score <7, 41% had adverse disease of which 100% were correctly identified by the test with a negative predictive value of 100% (95% confidence interval, 86–100%).

Conclusions:

This urine-based test accurately identifies men with clinical low-risk disease who do not have adverse pathology in their prostates and would be excellent candidates for active surveillance.

Evaluation of models predicting insignificant prostate cancer to select men for active surveillance of prostate cancer

BACKGROUND

In an era of personalized medicine, individualized risk assessment using easily available tools on the internet and the literature are appealing. However, uninformed use by clinicians and the public raises potential problems. Herein, we assess the performance of published models to predict insignificant prostate cancer (PCa), using a multi-national low-risk population that may be considered for active surveillance (AS) based on contemporary practice.

METHODS

Data on men suitable for AS but undergoing upfront radical prostatectomy were pooled from three international academic institutions in Cambridge (UK), Toronto (Canada) and Melbourne (Australia). Four predictive models identified from literature review were assessed for their ability to predict the presence of four definitions of insignificant PCa. Evaluation was performed using area under the curve (AUC) of receiver operating characteristic curves and Brier scores for discrimination, calibration curves and decision curve analysis.

RESULTS

A cohort of 460 men meeting the inclusion criteria of all four nomograms was identified. The highest AUCs calculated for any of the four models ranged from 0.618 to 0.664, suggesting weak positive discrimination at best. Models had best discriminative ability for a definition of insignificant disease characterized by organ-confined Gleason score ⩽6 with a total volume ⩽0.5 ml or 1.3 ml. Calibration plots showed moderate range of predictive ability for the Kattan model though this model did not perform well at decision curve analysis.

CONCLUSIONS

External assessment of models predicting insignificant PCa showed moderate performance at best. Uninformed interpretation may cause undue anxiety or false reassurance and they should be used with caution.

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.

CCL2 promotes integrin-mediated adhesion of prostate cancer cells in vitro

PURPOSE

Chemokines undergo alterations during neoplasia. However, knowledge about their functional significance in prostate cancer (PCa) progression is still sparse. Since chemokine (C-C motif) ligand 2 (CCL2) is significantly up-regulated in patients with PCa, aim of the current study was to assess whether CCL2 contributes to invasive behavior of prostate cancer cells in vitro.

METHODS

The human PCa cell line PC3 was stimulated with CCL2. Cell growth was investigated by MTT dye reduction assay. Cell adhesion was analyzed by measuring attachment to a human endothelial cell (HUVEC) monolayer and immobilized collagen. Cell migration was assessed by a chemotactic assay. Integrin expression on the cell surface was evaluated by Western blot. Blocking studies were performed with anti-integrin α3, anti-integrin α6 and anti-integrin β4 monoclonal antibodies.

RESULTS

PC3 cell growth 72 h after CCL2 exposure was significantly increased, compared to controls. Activation of tumor cells by CCL2 significantly enhanced tumor cell adhesion to HUVEC and immobilized collagen. CCL2, added for 4 or 24 h, elevated α6 and β4 (4 > 24 h) integrin expression. α3 was enhanced after 4 h, but reduced after 24 h. Blocking either α3, α6 or β4 led to significant suppression of tumor cell binding to immobilized collagen.

CONCLUSIONS

CCL2 stimulates PCa cell adhesion and induces alterations in α3-, α6- and β4-integrin expression on the cell surface. Blocking these integrins leads to a significant reduction in cell adhesion.

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.