Circulating biomarkers for prostate cancer

Evaluation of prediction models for the staging of prostate cancer

Background

There are dilemmas associated with the diagnosis and prognosis of prostate cancer which has lead to over diagnosis and over treatment. Prediction tools have been developed to assist the treatment of the disease.

Methods

A retrospective review was performed of the Irish Prostate Cancer Research Consortium database and 603 patients were used in the study. Statistical models based on routinely used clinical variables were built using logistic regression, random forests and k nearest neighbours to predict prostate cancer stage. The predictive ability of the models was examined using discrimination metrics, calibration curves and clinical relevance, explored using decision curve analysis. The N = 603 patients were then applied to the 2007 Partin table to compare the predictions from the current gold standard in staging prediction to the models developed in this study.

Results

30% of the study cohort had non organ-confined disease. The model built using logistic regression illustrated the highest discrimination metrics (AUC = 0.622, Sens = 0.647, Spec = 0.601), best calibration and the most clinical relevance based on decision curve analysis. This model also achieved higher discrimination than the 2007 Partin table (ECE AUC = 0.572 & 0.509 for T1c and T2a respectively). However, even the best statistical model does not accurately predict prostate cancer stage.

Conclusions

This study has illustrated the inability of the current clinical variables and the 2007 Partin table to accurately predict prostate cancer stage. New biomarker features are urgently required to address the problem clinician’s face in identifying the most appropriate treatment for their patients. This paper also demonstrated a concise methodological approach to evaluate novel features or prediction models.

Differences in characteristics of men with localised prostate cancer who demonstrate low, intermediate or high prostate-specific antigen velocity

BACKGROUND

Current diagnostic tools are inadequate for reliable prediction of prostate cancer (PCa) aggressiveness in patients with localised disease. This results in many patients being exposed to potentially unnecessary invasive treatment and its associated morbidities. In order to develop appropriate treatment strategies, it is essential to understand the differences between patients who will develop aggressive disease and those who will not.

METHODS

A longitudinal study was conducted in men with localised PCa on active surveillance for their disease in which 140 subjects were followed every 3 months for up to 5 years. Change in prostate-specific antigen (PSA) over time (PSA velocity) was used as a marker for PCa progression. Subjects were categorised as slow, intermediate and fast progressors based on tertiles of PSA velocity. Differences in baseline markers were investigated using logistic regressions. Two approaches were used, slow progressors were compared with fast progressors (model 1) and slow progressors were compared with combination of intermediate and fast progressors (model 2).

RESULTS

Aspirin was negatively associated with high PSA velocity in model 1 (odds ratio (95% confidence interval): 0.24 (0.06, 0.94), P-value = 0.04) and model 2 (odds ratio = 0.22 (0.08, 0.59), P-value = 0.003), whereas smoking was positively associated with high PSA velocity in model 1 (1.03 (0.92, 1.13), P-value = 0.01).

CONCLUSIONS

These findings highlight the role of aspirin and smoking in PCa progression. They have potential towards risk stratification as well as PCa prevention and hence need to be investigated further.

Synthesis and in vitro evaluation of MR molecular imaging probes using J591 mAb-conjugated SPIONs for specific detection of prostate cancer

Carcinoma of the prostate is the most frequent diagnosed malignant tumor in men and is the second leading cause of cancer-related death in this group. The cure rate of prostate cancer is highly dependent on the stage of disease at the diagnosis and early detection is key to designing effective treatment strategies. The objective of the present study is to make a specific MR imaging probe for targeted imaging of cancer cells. We take advantage of the fact that many types of prostate cancer cells express high levels of prostate-specific membrane antigen (PSMA) on their cell surface. The imaging strategy is to use superparamagnetic iron oxide nanoparticles (SPIONs), attached to an antibody (J591) that binds to the extracellular domain of PSMA, to specifically enhance the contrast of PSMA-expressing prostate cancer cells. Conjugation of mAb J591 to commercial SPIONs was achieved using a heterobifunctional linker, sulfo-SMCC. Two types of prostate cancer cell lines were chosen for experiments: LNCaP (PSMA+) and DU145 (PSMA-). MRI and cell uptake experiments demonstrated the high potential of the synthesized nanoprobe as a specific MRI contrast agent for detection of PSMA-expressing prostate cancer cells.

Controversies in using urine samples for Prostate Cancer detection: PSA and PCA3 expression analysis

PURPOSE

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies in the world. Although PSA utilization as a serum marker has improved prostate cancer detection it still presents some limitations, mainly regarding its specificity. The expression of this marker, along with the detection of PCA3 mRNA in urine samples, has been suggested as a new approach for PCa detection. The goal of this work was to evaluate the efficacy of the urinary detection of PCA3 mRNA and PSA mRNA without performing the somewhat embarrassing prostate massage. It was also intended to optimize and implement a methodological protocol for this kind of sampling.

MATERIALS AND METHODS

Urine samples from 57 patients with suspected prostate disease were collected, without undergoing prostate massage. Increased serum PSA levels were confirmed by medical records review. RNA was extracted by different methods and a preamplification step was included in order to improve gene detection by Real-Time PCR.

RESULTS

An increase in RNA concentration with the use of TriPure Isolation Reagent. Despite this optimization, only 15.8% of the cases showed expression of PSA mRNA and only 3.8% of prostate cancer patients presented detectable levels of PCA3 mRNA. The use of a preamplification step revealed no improvement in the results obtained.

CONCLUSION

This work confirms that prostate massage is important before urine collection for gene expression analysis. Since PSA and PCA3 are prostate specific, it is necessary to promote the passage of cells from prostate to urinary tract, in order to detect these genetic markers in urine samples.

Meta-analysis of genome-wide and replication association studies on prostate cancer

BACKGROUND

Genome-wide and replication association studies (GWAs) have identified multiple loci at which common variants modestly influence the risk of developing prostate cancer (PCa). To enhance the power to identify loci associated with PCa, we constructed a meta-analysis of GWAs on PCa.

METHODS

Articles evaluating the effects of genome-wide SNPs on PCa were identified by searching the PubMed database. After extraction of relevant data, main and subgroup meta-analyses were performed to assess the effects of relevant SNPs on PCa.

RESULTS

21 eligible articles containing 71 subgroups were included in this meta-analysis. Significant associations were found between 31 SNPs and PCa. They were rs445114, rs620861, rs983085, rs1016343, rs1447295, rs1859962, rs2660753, rs2710646, rs2735839, rs3760511, rs4242382, rs4430796, rs4962416, rs5945572, rs5945619, rs6470494, rs6501455, rs6983267, rs6983561, rs7000448, rs7214479, rs7501939, rs7920517, rs7931342, rs9364554, rs9623117, rs10090154, rs10486567, rs10896449, rs10993994, and rs16901979. The weighted odds ratios for above SNPs ranged between 0.64 and 1.88 (all P < 0.05). Subgroup analysis further indicated that the significant associations of some SNPs existed only in specific ancestry population (P < 10⁻⁵).

CONCLUSIONS

The current meta-analysis demonstrated the moderate effects of above 31 SNPs on PCa and 14 independent PCa risk loci were identified.

Biomarkers for prostate cancer detection

Since its approval by the US FDA in 1986, prostate-specific antigen (PSA) has been employed to monitor men with a diagnosis of prostate cancer. In 1994, PSA was approved for use in prostate cancer screening and has been employed worldwide. However, due to the limited specificity of PSA for the disease, novel biomarkers are needed for detecting prostate cancer and for determining which cancers need to be treated. This review will discuss the development of new biomarkers for prostate cancer detection and disease prognostication, focusing on recent progress and particular topical issues related to the development and validation of these new markers.

Optoacoustic imaging of the prostate: development toward image-guided biopsy

Optoacoustic (OA) tomography has demonstrated utility in identifying blood-rich malignancies in breast tissue. We describe the development and characterization of a laser OA imaging system for the prostate (LOIS-P). The system consists of a fiber-coupled Q-switched laser operating at 757 nm, a commercial 128-channel ultrasonic probe, a digital signal processor, and software that uses the filtered radial back-projection algorithm for image reconstruction. The system is used to reconstruct OA images of a blood-rich lesion induced in vivo in a canine prostate. OA images obtained in vivo are compared to images acquired using ultrasound, the current gold standard for guiding biopsy of the prostate. Although key structural features such as the urethra could be identified with both imaging techniques, a bloody lesion representing a highly vascularized tumor could only be clearly identified in OA images. The advantages and limitations of both forward and backward illumination modes are also evaluated by collecting OA images of phantoms simulating blood vessels within tissue. System resolution is estimated to be 0.2 mm in the radial direction of the acoustic array. The minimum detectable pressure signal is 1.83 Pa. Our results encourage further development toward a dual-modality OA/ultrasonic system for prostate imaging and image-guided biopsy.

Molecular biomarkers in prostate cancer

BACKGROUND

After more than two decades of clinical use, serum prostate-specific antigen (PSA) has increased the early diagnosis of prostate cancer, detecting the disease even when small volumes are present. Although stage migration of prostate cancer has occurred, PSA has well-known limitations, despite attempts at refinement and modification, such as the use of PSA velocity, which have been used to improve it. New biomarkers for prostate cancer have been discovered, with promising early results.

OBJECTIVE/METHODS

This article reviews the ubiquitous current literature on biomarkers in prostate cancer. A search using MEDLINE and EMBASE databases was performed and those articles reporting biomarkers in prostate cancer with clinically significant findings in terms of detection were analyzed. Immunohistochemical markers were not considered for this review.

RESULTS/CONCLUSION

Despite many markers being promising, no single marker has satisfied the criteria as a perfect candidate. Limited clinical use of IL-6, TGF-β1 and PCA3 has commenced, and further widespread availability of these tests is expected in the coming years. The future lies in artificial neural networks and panels of markers instead of individual assays. Although PSA has some well-known limitations, it is at present the best marker available for prostate cancer when used in conjunction with nomograms or risk calculators.

Prostate cancer diagnosis: should patients with prostate specific antigen >10ng/mL have stratified prostate biopsy protocols?

BACKGROUND

Trans-rectal ultrasound (TRUS) guided systematic prostate biopsy is a standard tool in prostate cancer (CaP) diagnosis. Extended biopsy techniques using 10-12 cores are the norm. Controversy exists on extended TRUS biopsy in men with PSA>10ng/mL. We evaluated cancer detection rates on an individual core basis, to stratify prostate biopsy protocols based on PSA levels.

PATIENTS AND METHODS

Over a five-year period, 1036 patients underwent TRUS guided prostate biopsy for raised serum PSA (>2.5ng/mL). 436 patients had PSA>10ng/mL. Patients with PSA<50ng/mL underwent a 12-core TRUS guided prostate biopsy including six peripheral biopsies. The six peripheral biopsies were directed laterally towards the base, mid-zone and apices. Remainder were standard para-sagittal sextant biopsies. Patients were stratified into three groups (PSA 10-20ng/mL, 20-50ng/mL and >50ng/mL).

RESULTS

Mean age of 436 patients with PSA>10ng/mL was 70.3years. 270 (62%) men had cancer. Cancer detection rates for different PSA levels were 46% (10-20ng/mL), 76% (20-50ng/mL) and 93% (>50ng/mL). Higher PSA levels and advanced clinical stage were associated with increased cancer detection rates. All patients with clinical T3 and T4 disease had biopsy diagnosed CaP.

CONCLUSION

TRUS guided prostate biopsy in patients with PSA>10ng/mL did not require 12 cores to diagnose CaP. CaP diagnosis required 8 cores in men with PSA 10-20ng/mL. These cores were right and left peripheral basal and apical, and right and left para-sagittal basal and apical biopsy. Only 6 cores were necessary to diagnose CaP in men with PSA>20ng/mL which were right and left peripheral basal and apical, and para-sagittal apical biopsies. We suggest limited TRUS prostate biopsy protocols for men with PSA>10ng/mL.

Identification of new genetic risk factors for prostate cancer

There is evidence that a substantial part of genetic predisposition to prostate cancer (PCa) may be due to lower penetrance genes which are found by genome-wide association studies. We have recently conducted such a study and seven new regions of the genome linked to PCa risk have been identified. Three of these loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK2/3. The MSMB and KLK2/3 genes may be useful for PCa screening, and the LMTK2 gene might provide a potential therapeutic target. Together with results from other groups, there are now 23 germline genetic variants which have been reported. These results have the potential to be developed into a genetic test. However, we consider that marketing of tests to the public is premature, as PCa risk can not be evaluated fully at this stage and the appropriate screening protocols need to be developed. Follow-up validation studies, as well as studies to explore the psychological implications of genetic profile testing, will be vital prior to roll out into healthcare.

Practical approaches to proteomic biomarkers within prostate cancer radiotherapy trials

INTRODUCTION

Proteomic biomarkers may be useful for monitoring therapeutic response and to triage cancer patients to best therapy.

OBJECTIVES

In this review, we highlight the importance of specimen acquisition, preparation and analysis in radiotherapy proteomic studies. We also discuss practical approaches for the design and execution of clinical proteomic studies using our recent experience based on specimens accrued during prostate cancer radiation therapy.

DISCUSSION AND CONCLUSIONS

Numerous proteomic methods are being employed, including high-throughput mass spectrometry and immunoassays, and using solid tissues, blood and urine for analysis. Given the potential complexity of cytokine and other protein responses, there is a need to assess proteomic signatures within serial samples as longitudinal studies during a course of fractionated radiotherapy (RT).

Zinc alpha 2-glycoprotein: a multidisciplinary protein

Zinc alpha 2-glycoprotein (ZAG) is a protein of interest because of its ability to play many important functions in the human body, including fertilization and lipid mobilization. After the discovery of this molecule, during the last 5 decades, various studies have been documented on its structure and functions, but still, it is considered as a protein with an unknown function. Its expression is regulated by glucocorticoids. Due to its high sequence homology with lipid-mobilizing factor and high expression in cancer cachexia, it is considered as a novel adipokine. On the other hand, structural organization and fold is similar to MHC class I antigen-presenting molecule; hence, ZAG may have a role in the expression of the immune response. The function of ZAG under physiologic and cancerous conditions remains mysterious but is considered as a tumor biomarker for various carcinomas. There are several unrelated functions that are attributed to ZAG, such as RNase activity, regulation of melanin production, hindering tumor proliferation, and transport of nephritic by-products. This article deals with the discussion of the major aspects of ZAG from its gene structure to function and metabolism.

Inflammation and CYP3A4-mediated drug metabolism in advanced cancer: impact and implications for chemotherapeutic drug dosing

BACKGROUND

The inability to accurately predict treatment outcomes for cancer patients in terms of tumour response and anticancer drug toxicity is a severe limitation inherent in current approaches to chemotherapy. Many anticancer drugs are metabolically cleared by cytochrome P450 3A4 (CYP3A4), the predominant CYP expressed in liver. CYP3A4 expression exhibits marked interindividual variation and is repressed in acute inflammatory states.

OBJECTIVES

(1) To review the relevance of CYP3A4 variability to drug metabolism in the setting of cancer and to understand how inflammation associated with malignancy contributes to both this variability and to adverse treatment outcomes. (2) To examine the relationship between tumour-induced inflammation and repression of CYP3A4 and to explore methods of dosing of anticancer drugs in the setting of advanced cancer.

METHODS

Review of relevant literature covering both human and animal studies as well as in vitro mechanistic studies.

RESULTS/CONCLUSIONS

Interindividual variability in CYP3A4 expression is a major confounding factor for effective cancer treatment and methods to predict CYP3A4-mediated drug clearance may have clinical utility in this setting. Although acute inflammation has long been recognised to repress drug metabolism, it is now becoming apparent that cancer patients exhibiting clinical and laboratory features of an inflammatory response have reduced expression of CYP3A4 and possibly other genes relevant to anticancer drug disposition.

PCA3: a molecular urine assay for predicting prostate biopsy outcome

PURPOSE

A urinary assay for PCA3, an mRNA that is highly over expressed in prostate cancer cells, has shown usefulness as a diagnostic test for this common malignancy. We further characterized PCA3 performance in different groups of men and determined whether the PCA3 score could synergize with other clinical information to predict biopsy outcome.

MATERIALS AND METHODS

Prospectively urine was collected following standardized digital rectal examination in 570 men immediately before prostate biopsy. Urinary PCA3 mRNA levels were quantified and then normalized to the amount of prostate derived RNA to generate a PCA3 score.

RESULTS

The percent of biopsy positive men identified increased directly with the PCA3 score. PCA3 assay performance was equivalent in the first vs previous negative biopsy groups with an area under the ROC curve of 0.70 and 0.68, respectively. Unlike serum prostate specific antigen the PCA3 score did not increase with prostate volume. PCA3 assay sensitivity and specificity were equivalent at serum prostate specific antigen less than 4, 4 to 10 and more than 10 ng/ml. A logistic regression algorithm using PCA3, serum prostate specific antigen, prostate volume and digital rectal examination result increased the AUC from 0.69 for PCA3 alone to 0.75 (p = 0.0002).

CONCLUSIONS

PCA3 is independent of prostate volume, serum prostate specific antigen level and the number of prior biopsies. The quantitative PCA3 score correlated with the probability of positive biopsy. Logistic regression results suggest that the PCA3 score could be incorporated into a nomogram for improved prediction of biopsy outcome. The results of this study provide further evidence that PCA3 is a useful adjunct to current methods for prostate cancer diagnosis.

Multiple newly identified loci associated with prostate cancer susceptibility

Prostate cancer is the most common cancer affecting males in developed countries. It shows consistent evidence of familial aggregation, but the causes of this aggregation are mostly unknown. To identify common alleles associated with prostate cancer risk, we conducted a genome-wide association study (GWAS) using blood DNA samples from 1,854 individuals with clinically detected prostate cancer diagnosed at </=60 years or with a family history of disease, and 1,894 population-screened controls with a low prostate-specific antigen (PSA) concentration (<0.5 ng/ml). We analyzed these samples for 541,129 SNPs using the Illumina Infinium platform. Initial putative associations were confirmed using a further 3,268 cases and 3,366 controls. We identified seven loci associated with prostate cancer on chromosomes 3, 6, 7, 10, 11, 19 and X (P = 2.7 x 10(-8) to P = 8.7 x 10(-29)). We confirmed previous reports of common loci associated with prostate cancer at 8q24 and 17q. Moreover, we found that three of the newly identified loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK3.

Serum markers for prostate cancer: a rational approach to the literature

INTRODUCTION

Due to its universal applicability for early detection and prediction of cancer stage and disease recurrence, widespread implementation of serum-based prostate-specific antigen (PSA) measurements has a significant influence on current treatment strategies for men with prostate cancer (PCa). However, over-detection and the resultant over-treatment of indolent cancers have been strongly implicated to occur. Using current recommended guidelines, the PSA test suffers from both limited sensitivity and specificity to enable efficacious population-based cancer detection. Therefore, novel biomarkers are much needed to complement PSA by enhancing its diagnostic and prognostic performance.

METHODS

The present literature on serum markers for PCa was reviewed. PSA derivatives, molecular PSA isoforms, and novel molecular targets in blood were summarized and weighted against their potential to improve decision-making of men with PCa.

RESULTS

Current evidence suggests that no single analyte is likely to achieve the desired level of diagnostic and prognostic accuracy for PCa. However, the combination of biomarkers with clinical and demographic data, for example, using established standard nomograms, has produced progress toward the goal of both optimal screening and risk assessment. Furthermore, potential candidate molecular markers for PCa can be derived from high-throughput technologies. Current studies demonstrate that understanding dynamic PSA changes over time may offer diagnostic and prognostic information.

CONCLUSIONS

Bridging the gap between basic science and clinical practice represents the main goal in the near future to enable physicians to tailor risk-adjusted screening and treatment strategies for current patients with PCa.

Reverse-Phase versus Sandwich Antibody Microarray, Technical Comparison from a Clinical Perspective

Protein microarrays are powerful tools to quantify and characterize proteins in multiplex assays. They have great potential within clinical diagnostics and prognostics, as they minimize consumption of both analyte and biological sample. Assays that do not require labeling of the biological specimen, henceforth called label-free, are vital for ease of clinical sample processing. Here, we evaluate two label-free techniques, reverse-phase and sandwich antibody assays, using microarrays on high-performance porous silicon surfaces and fluorescence detection. In view of increasing interest in reverse microarrays, this paper focuses on analytical sensitivity of the reverse assays compared to the more complex but highly sensitive sandwich assay. Sensitivity, linear range, and reproducibility of the two assays were compared using prostate-specific antigen (PSA) in buffer. The sandwich assay displayed 5 orders of magnitude lower detection limit (0.7 ng/mL) compared to the reverse assay (70 microg/mL). PSA at 50 nM (1.5 microg/mL) in cell lysates was detected by the sandwich assay but not by the reverse assay, demonstrating again a far lower detection limit for sandwich microarrays. In independent assay runs of PSA spiked in female serum, the sandwich assay had good linearity (R2 > 0.99) and reproducibility (coefficient of variation < or =15%), and the detection limit could be improved to 0.14 ng/mL. Without further signal amplification, the sandwich assay would be our choice for PSA analysis of clinical samples using a microarray technology platform.