Prostate-specific antigen

Serum levels of prostate specific antigen, free PSA, [-2]proPSA, fPSA/tPSA ratio, Prostate Health Index, and glycosylation patterns of free PSA in patients with benign prostatic hyperplasia pharmacotherapy

BACKGROUND

The medication used to treat benign prostate hyperplasia (BPH), a common condition in men over 50 years of age, can alter the levels of biomarkers used in prostate cancer detection. Commonly used medications for BPH include alpha-blockers, 5-alpha reductase inhibitors (5-ARIs), and muscarinic antagonists. We studied the impact of these drugs on total prostate-specific antigen (tPSA), free PSA (fPSA), [-2]proPSA, fPSA/tPSA ratio, and the Prostate Health Index (PHI), as well as novel potential biomarkers in the form of glycan composition of fPSA.

PATIENTS AND METHODS

Serum samples were collected from 564 males with BPH, with a mean age of 68.5 years. The samples were used to measure levels of tPSA, fPSA, and [-2]proPSA. The fPSA/tPSA and PHI were then calculated. The glycan composition of fPSA was analyzed using lectin-based glycoprofiling. Pharmacotherapy data was collected from the patients' medical records.

RESULTS

Alpha-blocker monotherapy was associated with higher fPSA and fPSA/tPSA ratio, and decreased PHI. Levels of tPSA were not impacted. Alpha-blocker and 5-ARI dual therapy was associated with reduced levels of fPSA, [-2]proPSA, and PHI. Therapy combining alpha-blockers and antimuscarinic agents did not significantly influence biomarker levels apart from an increase in a Maackia amurensis lectin-recognized glycan originating in fPSA.

CONCLUSION

BPH pharmacotherapy notably affects prostate cancer biomarkers. Recognizing the impact of pharmacotherapy is crucial for achieving an accurate diagnosis of prostate cancer and for planning treatment.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL

PURPOSE

The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort.

METHODS

This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort.

RESULTS

In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed.

CONCLUSION

PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Elevation of Serum Prostate-Specific Antigen Levels in Males With Pulmonary Embolism

Hypoxemia is a clinical characteristic of pulmonary embolism (PE). Hypoxemia is associated with variations in serum prostate-specific antigen (PSA) levels. Thus, the present study aimed to determine serum PSA levels in patients with PE, which may be helpful in improving clinical evaluation in screening for prostate diseases in those with PE. Clinical data from 61 consecutive male patients with PE and 113 age-matched healthy male controls were retrospectively analyzed. The pulmonary artery obstruction index (PAOI) was used to evaluate the pulmonary embolic burden. Compared with healthy controls, serum total PSA (tPSA) levels were significantly increased (P = .003), and free PSA (fPSA)/tPSA ratio was significantly decreased in patients with PE (P < .001). There was no significantly difference in serum fPSA levels between patients with PE and healthy controls (P = .253). A significant positive association was observed between serum tPSA levels and PAOI in patients with PE (β = .270, P = .036). Multivariable linear regression analysis revealed that serum tPSA levels were independently associated with PAOI in patients with PE (β = .347, P = .003). Serum tPSA levels were higher in male patients with PE than those in healthy controls, but fPSA was not affected. These findings highlight that PE may elevate serum tPSA levels, and that measures of tPSA should be interpreted with caution in screening for prostate diseases in patients with PE.

Beyond glyco-proteomics-Understanding the role of genetics in cancer biomarkers

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.

Locus-Specific Bisulfate NGS Sequencing of GSTP1, RNF219, and KIAA1539 Genes in the Total Pool of Cell-Free and Cell-Surface-Bound DNA in Prostate Cancer: A Novel Approach for Prostate Cancer Diagnostics

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539, also known as FAM214B) in the total pool of blood cell-free DNA, including cell-free DNA from plasma and cell-surface-bound DNA, of patients with prostate cancer and healthy donors was studied on the MiSeq platform. Our study found a higher methylation index of loci for total cell-free DNA compared with cell-free DNA. For total cell-free DNA, the methylation of GSTP1 in each of the 11 positions provided a complete separation of cancer patients from healthy donors, whereas for cell-free DNA, there were no positions in the three genes allowing for such separation. Among the prostate cancer patients, the minimum proportion of GSTP1 genes methylated in any of the 17 positions was 12.1% of the total circulated DNA fragments, and the minimum proportion of GSTP1 genes methylated in any of the 11 diagnostically specific positions was 8.4%. Total cell-free DNA was shown to be more convenient and informative as a source of methylated DNA molecules circulating in the blood than cell-free DNA.

Assessing volatile organic compounds exposure and prostate-specific antigen: National Health and Nutrition Examination Survey, 2001-2010

Background

Volatile organic compounds (VOCs) are a large group of chemicals widely used in people's daily routines. Increasing evidence revealed the VOCs' accumulating toxicity. However, the VOCs toxicity in male prostate has not been reported previously. Thus, we comprehensively evaluated the association between VOCs and prostate-specific antigen (PSA).

Methods

A total of 2016 subjects were included in our study from the National Health and Nutrition Examination Survey with VOCs, PSA, and other variables among U.S. average population. We constructed XGBoost Algorithm Model, Regression Model, and Generalized linear Model (GAM) to analyze the potential association. Stratified analysis was used to identify high-risk populations.

Results

XGBoost Algorithm model identified blood chloroform as the most critical variable in the PSA concentration. Regression analysis suggested that blood chloroform was a positive association with PSA, which showed that environmental chloroform exposure is an independent risk factor that may cause prostate gland changes [β, (95% CI), P = 0.007, (0.003, 0.011), 0.00019]. GAM observed the linear relationship between blood chloroform and PSA concentration. Meanwhile, blood chloroform linear correlated with water chloroform in the lower dose range, indicating that the absorption of water may be the primary origin of chloroform. Stratified associations analysis identified the high-risk group on the chloroform exposures.

Conclusion

This study revealed that blood chloroform was positively and independently associated with total PSA level, suggesting that long-term environmental chloroform exposure may cause changes in the prostate gland.

PSA response rate as a surrogate marker for median overall survival in docetaxel-based first-line treatments for patients with metastatic castration-resistant prostate cancer: an analysis of 22 trials

The aim of this study was to determine the correlation between PSA response rate (PSA RR) and overall survival (OS) and identify PSA RR as a potential surrogate for OS, in docetaxel-based first-line treatments for castration-resistant prostate cancer (CRPC). Trials of first-line regimens with docetaxel for patients with metastatic CRCP published between 2004 and 2013 were identified, and data were evaluated statistically in order to investigate the correlation between PSA RR and OS. A total of 22 trials were identified and included in our analysis, for a total of 7,677 patients. In addition, we divided all the trails and arms of the randomized trials in two subgroups, the first one composed only of docetaxel (D) plus prednisone (P) regimens (standard therapy) and the second one composed of all D + other drug combinations (D combinations). Analysing all the trials and arms as a single unit, we found a statistically significant correlation between PSA RR and OS, with Spearman's rank correlation coefficient ρ = 0.50 (95% confidence interval (CI), 0.47 to 0.88) (P = 0.003). Also evaluating the standard therapy group, we found a statistically significant correlation between PSA RR and OS, with Spearman's ρ = 0.65 (95% CI, 0.38 to 0.70) (P = 0.02). However, when we assessed the D combination group, we found Spearman's rank correlation coefficient decreased (ρ = 0.42) (95% CI, 0.28 to 0.80) and resulted nonstatistically significant (P = 0.06). In conclusion, we found a statistically significant correlation between PSA RR and OS. The usage of PSA RR as a surrogate marker for OS in metastatic CRPC patients treated with D-based first-line regimens may be appropriate only in the D + P combination.

Potential ethnic modifiers in the assessment and treatment of Alzheimer's disease: challenges for the future

OBJECTIVE

Despite numerous clinical trials, it is unknown whether ethnicity affects treatment response to cognitive enhancers in Alzheimer's disease (AD). There is convincing evidence of ethnic and genetic variability in drug metabolism. This article reviews the available data on ethnicity in clinical trials for AD to answer two questions: (1) what are the challenges to diagnose and treat AD across different ethnic groups, and (2) are there differences in response to pharmacologic interventions for AD across these different ethnic groups?

METHOD

Available data from Alzheimer's Disease Cooperative Study (ADCS) randomized controlled clinical trials and from randomized controlled industry-sponsored trials for four cognitive enhancers (donepezil, galantamine, rivastigmine and sabeluzole) were pooled to assess the numbers of non-Caucasian participants.

RESULTS

The participation of ethnic minority subjects in clinical trials for AD was dependent on the funding source, although Caucasian participants were over-represented and non-Caucasian participants were under-represented in the clinical trials. Because of the low participation rate of ethnic minorities, there were insufficient data to assess any differences in treatment outcome among different ethnic groups. Strategies to improve diversity in clinical trials are discussed.

CONCLUSION

Greater participation of ethnically diverse participants in clinical trials for AD would generate additional information on possible differences in metabolism, treatment response, adverse events to therapeutic agents, and could foster the investigation of genetic variability among ethnic groups.

Immunology and immunotherapy approaches for prostate cancer

Several mechanisms that impair the immune response to promote tumour progression are reported. These mechanisms aim to reduce the ability of antigen-presenting cells to present antigen and activate naïve T cells to support an active immune response or to create a suppressive environment that induce non-functional tumour-associated antigen-specific T cells. Prostate cancer (PC) alone accounts for 33% of incident cancer cases and about 9% of all cancer-related deaths among men in the USA during 2006. Whereas androgen deprivation has remained the first line of therapy for advanced PC, other therapies are still required due to progression to an androgen-resistant state and eventually loss of control in patients receiving hormonal therapy. Immunotherapy seems to be a promising approach to enhance tumour-specific T-cell responses in different cancers including prostate. More importantly, clinical trials in advanced PC patients have shown that immunotherapy may generate significant clinical responses. Immunology and immunotherapy aspects of PC with focus on prostate-specific antigen will be presented.

Carcinoembryonic antigen, alpha-fetoprotein, and prostate-specific antigen in the sera of industrial workers exposed to phenol, formaldehyde, urea, and mixed vapors

Exposure to certain industrial agents has been thought to have carcinogenic potential, both for employees who work closely with agents and for the general population that comes into contact with them. The objective of the present study is to evaluate the changes at the cellular level or at the level of cellular metabolism products present in the biological fluid, and to detect early stages of the carcinogenic process resulting from the exposure of industrial environmental hazards. Carcinoembryonic antigen (CEA), alpha-fetoproteins (AFP), and prostate-specific antigen (PSA) were measured in sera of workers (n = 51), who were divided into 4 groups: group I, workers exposed to phenol; group II, workers exposed to formaldehyde; group III, workers exposed to urea; and group IV, workers exposed to mixed vapor, plus a reference control healthy group (n = 15). The results showed that 75% of the workers exposed to phenol, 75% of the workers exposed to urea, 83.3% of workers exposed to formalin, and 92.3% of the workers exposed to mixed vapors had raised values of serum CEA (S-CEA) above normal value of the control group. Also, 23% of workers exposed to mixed vapors, 44% of workers exposed to formalin, 50% of workers exposed to phenol, and 62.5% of workers exposed to urea had raised values of serum AFP (S-AFP) above normal value of control group. Finally, 16.6% of workers exposed to phenol, 23% of workers exposed to mixed vapors, and 33.3% of workers exposed to formalin had raised values of serum PSA (S-PSA) above the normal value of control group; there were no raised values of S-PSA in workers exposed to urea. No significant difference was found in the activities of AST and ALT in group I, but a highly significant increase was found in the AST activities for groups II and IV and the ALT activities for groups III and IV. A significant difference was found in the activity of ALT in group II and in AST for group III. There was no significant difference in the levels of albumin in groups I, II, and III, whereas albumin levels were significantly decreased in group IV. No significant change was found in the level of urea and creatinine in all groups except for group III, where serum levels of creatinine were significantly decreased. From our findings, we concluded that S-CEA can be used as an important prognostic screening marker for early prediction for malignancy, and for management of workers with lung cancer who are exposed to the environmental hazards in industrial factories. Furthermore, S-AFP can be used also as a biomarker if it is carried out and correlated with S-CEA.

Inhibition of CWR22Rnu1 tumor growth and PSA secretion in athymic nude mice by green and black teas

Cancer of the prostate gland (CaP), the most common invasive malignancy and a major cause of cancer related deaths in male population in the USA, is an ideal candidate disease for chemoprevention because it is typically detected in elderly population with a relatively slower rate of growth and progression. Many dietary phytochemicals are showing promising chemopreventive effects, at-least in pre-clinical models of CaP. Our published data in cell culture and animal studies, supported by the work from other laboratories, as well as epidemiological observations and case-control studies, suggest that polyphenols present in green tea possess CaP chemopreventive and possibly therapeutic effects. This present study was designed to compare CaP cancer chemopreventive effects of green tea polyphenols (GTP), water extract of black tea, and their major constituents epigallocatechin-3-gallate and theaflavins, respectively, in athymic nude mice implanted with androgen-sensitive human CaP CWR22Rnu1 cells. Our data demonstrated that the treatment with all the tea ingredients resulted in (i) significant inhibition in growth of implanted prostate tumors, (ii) reduction in the level of serum prostate specific antigen, (iii) induction of apoptosis accompanied with upregulation in Bax and decrease in Bcl-2 proteins, and (iv) decrease in the levels of VEGF protein. Furthermore, we also found that GTP (0.01 or 0.05% w/v; given after establishment of CWR22Rnu1 tumor) causes a significant regression of tumors suggesting therapeutic effects of GTP at human achievable concentrations.

Advancing cancer biotherapy with proteomics

Proteomics is becoming increasingly important for cancer biotherapy. The development of high-throughput platforms now allows the analysis of multiple proteins from small quantities of material. While these techniques are being used to discover new biomarkers, they are particularly important for assessing complex biologic processes such as immunotherapy for cancer. Recent advances in this field are reviewed, as well as the use of proteomics to assess the effectiveness and toxicities of high-dose IL-2 cancer therapy. Proteomics is becoming useful in assessing cancer biotherapies and in unraveling their mechanisms of action. High-throughput proteomic technologies have now advanced to a stage where they have the potential to become effective discovery tools for biomarkers/predictors of disease, disease recurrence, and response to therapy.

Is Prostate-Specific Antigen a Valid Surrogate End Point for Survival in Hormonally Treated Patients With Metastatic Prostate Cancer? Joint Research of the European Organisation for Research and Treatment of Cancer, the Limburgs Universitair Centrum, and AstraZeneca Pharmaceuticals

Purpose

The long duration of phase III clinical trials of overall survival (OS) slows down the treatment-development process. It could be shortened by using surrogate end points. Prostate-specific antigen (PSA) is the most studied biomarker in prostate cancer (PCa). This study attempts to validate PSA end points as surrogates for OS in advanced PCa.

Patients and Methods

Individual data from 2,161 advanced PCa patients treated in studies comparing bicalutamide to castration were used in a meta-analytic approach to surrogate end-point validation. PSA response, PSA normalization, time to PSA progression, and longitudinal PSA measurements were considered.

Results

The known association between PSA and OS at the individual patient level was confirmed. The association between the effect of intervention on any PSA end point and on OS was generally low (determination coefficient, < 0.69).

Conclusion

It is a common misconception that high correlation between biomarkers and true end point justify the use of the former as surrogates. To statistically validate surrogate end points, a high correlation between the treatment effects on the surrogate and true end point needs to be established across groups of patients treated with two alternative interventions. The levels of association observed in this study indicate that the effect of hormonal treatment on OS cannot be predicted with a high degree of precision from observed treatment effects on PSA end points, and thus statistical validity is unproven. In practice, non-null treatment effects on OS can be predicted only from precisely estimated large effects on time to PSA progression (TTPP; hazard ratio, < 0.50).

Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml

PURPOSE

Artificial intelligence based pattern recognition algorithms have been developed and successfully used to analyze complex serum proteomic data streams generated by surface enhanced, laser desorption ionization time-of-flight mass spectroscopy. In the current study we used a high performance, hybrid quadrupole time-of-flight mass spectrometer to generate discriminatory serum proteomic profiles to determine if this technology could be used to determine the need for prostate biopsy in men with elevated prostate specific antigen (PSA).

MATERIALS AND METHODS

Serum samples were collected from 154 men with serum PSA 2.5 to 15.0 ng/ml and/or abnormal digital rectal examination prior to transrectal ultrasound guided biopsy. Serum samples were applied to WCX2 (weak cation exchange protein chip) Protein Arrays (Ciphergen Biosystems, Fremont, California) by a Biomek 2000 robotic liquid handler (Beckman-Coulter, Chaska, Minnesota) and low molecular weight (less than 20 kDa) proteomic patterns were generated with an API QSTAR Pulsar i LC/MS/MS System (Applied Biosystems, Framingham, Massachusetts). High resolution mass spectra were analyzed with a pattern recognition bioinformatics tool, that is Proteome Quest beta version 1.0 (Correlogic Systems, Inc., Bethesda, Maryland), in an attempt to identify and discover key discriminating ion signatures. Serum samples from 63 men (2 or more negative prostate biopsies in 23, 1 negative biopsy in 10 and biopsy detected prostate cancer [CaP] in 30) were used to train the diagnostic algorithm. The remaining 91 samples, including 28 of prostate cancer and 63 of 1 or more negative biopsies, were analyzed in blinded fashion.

RESULTS

The most discriminatory model was found using the WCX2 chip. Testing the remaining 91 men with this model yielded 100% sensitivity and 67% specificity. In other words, if the proteomic pattern had been used to determine the need for prostate biopsy in this cohort of men with PSA between 2.5 and 15.0 ng/ml, 67% (42 of 63) with negative biopsies would have avoided unnecessary biopsy, while no cancers would have been missed.

CONCLUSIONS

Our data demonstrate that high resolution mass spectroscopy can generate serum proteomic patterns that discriminate men with elevated PSA due to benign processes from men with CaP even when PSA is within the diagnostic gray zone. We are currently expanding the testing set to determine the reliability of this new technology to decrease unnecessary prostate biopsies without compromising the detection of curable CaP.

Clinical proteomics: Applications for prostate cancer biomarker discovery and detection

The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis.

The role of surrogate markers in the clinical development of antiretroviral therapy: a model for early evaluation of targeted cancer drugs

Both CD4 cell counts and measurements of plasma HIV-1 RNA (i.e. viral load) have become established surrogate markers for predicting treatment and disease outcome in HIV infection, and are instrumental for the evaluation of new antiretroviral drugs in clinical trials. Recently, HIV drug-resistance testing has also become available and has been shown to have prognostic value in providing guidance with antiretroviral therapy. The identification of robust surrogate markers is also an essential requirement for the clinical development of targeted anticancer agents, which unlike their cytotoxic counterparts, are often devoid of the toxicities that have been traditionally used to monitor the efficacy of chemotherapy. In particular, biological or molecular markers that are predictive of a drug effect need to be integrated into early efficacy trials of targeted therapies in order to confirm that the drug is in fact "hitting" the intended target. The full clinical significance of many of the altered cell types or polymorphisms, which are selected by cytostatic agents, remains to be elucidated. However, molecular genotyping of these targets, akin to drug resistance testing for HIV infection, may constitute an important strategy to assist with the selection and monitoring of targeted chemotherapy in cancer patients. Thus, lessons from HIV/AIDS on the value of surrogate makers may assist with the development and optimization of targeted cancer therapy.

How to improve prostate biopsy detection of prostate cancer

The combination of serum prostate-specific antigen (PSA) testing and transrectal ultrasonography is a highly effective strategy to diagnose prostate cancer at an early curable stage. Even though PSA is the most useful serum biomarker to aid in prostate cancer detection, it has limited specificity: as many as 75% of men who undergo prostate biopsy because of an elevated PSA do not have prostate cancer. Additionally, sextant prostate biopsies miss prostate cancer at least 20% of the time. To reduce the number of false-negative biopsies, many have advocated obtaining 12 or more cores in a single biopsy session. Studies have shown that this practice is safe and can enhance cancer detection modestly. Although it is unlikely that prostate cancer imaging will replace prostate biopsy in the near future, many exciting new imaging technologies should eventually improve targeting of prostate needle biopsy and reduce false-negative biopsies. Some of the most exciting areas include power Doppler sonography, microbubble intravenous ultrasound contrast agents, and magnetic resonance spectroscopy. These functional imaging modalities can assess tumor blood flow and metabolic activity at a cellular level and can detect malignant changes that may not be detected by standard anatomic imaging.