Zinc α2-glycoprotein as a potential novel urine biomarker for the early diagnosis of prostate cancer

Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine

As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002-2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.

Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

Simple Summary

Prostate cancer (PCa) is one of the most common cancers. Due to the limited and invasive approaches for PCa diagnosis, it is crucial to identify more accurate and non-invasive biomarkers for its detection. The aim of our study was to non-invasively uncover new protein targets for detecting PCa using a proteomics and proteogenomics approach. This work identified several dysregulated mutant protein isoforms in urine from PCa patients, some of them predicted to have a protective or an adverse role in these patients. These results are promising given urine’s non-invasive nature and offers an auspicious opportunity for research and development of PCa biomarkers.

Abstract

To identify new protein targets for PCa detection, first, a shotgun discovery experiment was performed to characterize the urinary proteome of PCa patients. This revealed 18 differentially abundant urinary proteins in PCa patients. Second, selected targets were clinically tested by immunoblot, and the soluble E-cadherin fragment was detected for the first time in the urine of PCa patients. Third, the proteogenome landscape of these PCa patients was characterized, revealing 1665 mutant protein isoforms. Statistical analysis revealed 6 differentially abundant mutant protein isoforms in PCa patients. Analysis of the likely effects of mutations on protein function and PPIs involving the dysregulated mutant protein isoforms suggests a protective role of mutations HSPG2*Q1062H and VASN*R161Q and an adverse role of AMBP*A286G and CD55*S162L in PCa patients. This work originally characterized the urinary proteome, focusing on the proteogenome profile of PCa patients, which is usually overlooked in the analysis of PCa and body fluids. Combined analysis of mass spectrometry data using two different software packages was performed for the first time in the context of PCa, which increased the robustness of the data analysis. The application of proteogenomics to urine proteomic analysis can be very enriching in mutation-related diseases such as cancer.

Integrating Serum Biomarkers into Prediction Models for Biochemical Recurrence Following Radical Prostatectomy

This study undertook to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy using serum biomarkers and clinical features. Three radical prostatectomy cohorts were used to build and validate a model of clinical variables and serum biomarkers to predict BCR. The Cox proportional hazard model with stepwise selection technique was used to develop the model. Model evaluation was quantified by the AUC, calibration, and decision curve analysis. Cross-validation techniques were used to prevent overfitting in the Irish training cohort, and the Austrian and Norwegian independent cohorts were used as validation cohorts. The integration of serum biomarkers with the clinical variables (AUC = 0.695) improved significantly the predictive ability of BCR compared to the clinical variables (AUC = 0.604) or biomarkers alone (AUC = 0.573). This model was well calibrated and demonstrated a significant improvement in the predictive ability in the Austrian and Norwegian validation cohorts (AUC of 0.724 and 0.606), compared to the clinical model (AUC of 0.665 and 0.511). This study shows that the pre-operative biomarker PEDF can improve the accuracy of the clinical factors to predict BCR. This model can be employed prior to treatment and could improve clinical decision making, impacting on patients' outcomes and quality of life.

Bioinformatic analysis of dysregulated proteins in prostate cancer patients reveals putative urinary biomarkers and key biological pathways

Prostate cancer (PCa) is one of the most common cancer types among men. The quantification of prostate-specific antigen used for PCa detection has revealed limited applicability. Thus, it is crucial to identify new minimally invasive biomarkers for PCa. It is believed that the integration of proteomics data from different studies is vital for identifying new biomarkers for PCa, but studies carried out in this regard have few converging results. Using a different approach, this study aimed to unveil molecular features consistently dysregulated in PCa and potential urinary biomarkers for PCa. The novelty of this analysis relies on the comparison of urinary and tissue proteomes from PCa patients and consequent exclusion of kidney and bladder cancer interference. The conducted bioinformatic analysis revealed molecular processes dysregulated in urine from PCa patients that mirror the alterations in prostate tumor tissue. To identify putative urinary biomarkers, proteins previously detected in kidney and bladder tissues were eliminated from the final list of potential urinary biomarkers for PCa. After a detailed analysis, MSMB, KLK3, ITIH4, ITIH2, HPX, GP2, APOA2 and AZU1 proteins stood out as candidate urinary biomarkers for PCa.

Urinary proteomic profiles of prostate cancer with different risk of progression and correlation with histopathological features

Prostate cancer (PCa) is the most common tumor in men with extremely variable outcome, varying from latent or indolent form to very aggressive behavior. High grade tumors, expansions exceeding the prostatic capsule into the surrounding soft tissues and spreading through lymph vascular channels, represent the most consistent unfavorable prognostic factors. However, accuracy in the prediction of the disease progression is sometimes difficult. Along with new molecular diagnostic techniques and more accurate histopathological approaches, proteomic studies challenge to identify potential biomarkers predictive of PCa progression. In our study we analyzed the urinary proteomes of 42 patients affected by PCa through two-dimensional electrophoresis associated with mass spectrometry. Proteomic profiles were correlated to histopathological features including pTNM stage and tumor differentiation in order to provide new promising markers able to define more accurately the PCa aggressiveness and driving new therapeutic approaches.

The Repertoire of Glycan Alterations and Glycoproteins in Human Cancers

Cancer as the leading cause of death worldwide has many issues that still need to be addressed. Since the alterations on the glycan compositions or/and structures (i.e., glycosylation, sialylation, and fucosylation) are common features of tumorigenesis, glycomics becomes an emerging field examining the structure and function of glycans. In the past, cancer studies heavily relied on genomics and transcriptomics with relatively little exploration of the glycan alterations and glycoprotein biomarkers among individuals and populations. Since glycosylation of proteins increases their structural complexity by several orders of magnitude, glycome studies resulted in highly dynamic biomarkers that can be evaluated for cancer diagnosis, prognosis, and therapy. Glycome not only integrates our genetic background with past and present environmental factors but also offers a promise of more efficient patient stratification compared with genetic variations. Therefore, studying glycans holds great potential for better diagnostic markers as well as developing more efficient treatment strategies in human cancers. While recent developments in glycomics and associated technologies now offer new possibilities to achieve a high-throughput profiling of glycan diversity, we aim to give an overview of the current status of glycan research and the potential applications of the glycans in the scope of the personalized medicine strategies for cancer.

The importance of plasma arginine level and its downstream metabolites in diagnosing prostate cancer

PURPOSE

There is still no certain threshold value of prostate-specific antigen (PSA) for prostate cancer diagnosis. We aimed to investigate the predictive value of arginine and its metabolites for diagnosing prostate cancer in patients with PSA 4-10 ng/ml and evaluate their usefulness as prognostic tumor markers.

METHODS

Seventy-eight patients with a mean age of 64.50 ± 5.49 years were included in our prospective observational study between November 2016 and March 2017. They were divided into two equal groups according to the pathologic results of prostate biopsy (benign vs. malignant). Plasma arginine and ornithine levels were analyzed before biopsy by liquid chromatography-tandem mass spectrometry. ELISA was used for analyzing urinary diacetylspermine.

RESULTS

In PSA-adjusted analysis, the malignant group had lower plasma arginine levels (p = 0.021) and arginine to ornithine ratio (AOR) (p = 0.010), but higher plasma ornithine levels (p = 0.012) and urinary diacetylspermine levels (p < 0.001) as compared with the benign group. While arginine (r = - 0.628, p < 0.001) and AOR (r = - 0.714, p < 0.001) were negatively correlated with D'Amico clinical classification (p < 0.001), ornithine (r = 0.659, p < 0.001) and diacetylspermine (r = 0.710, p < 0.001) were found to be positively correlated (p < 0.001). In multivariate analysis, ornithine [OR 3.264, 95% CI (1.045-10.196), p = 0.042] and diacetylspermine [OR 6.982, 95% CI (2.403-20.290), p < 0.001] were found to be more significant in detection of prostate cancer.

CONCLUSION

Plasma arginine, ornithine, AOR and urinary diacetylspermine levels may be used as molecular markers to predict prostate biopsy outcomes in patients with PSA 4-10 ng/ml. But according to our results, the use of ornithine and diacethylspermine prior to biopsy seems to be the most cost-effective diagnostic strategy.

Predictive value of AZGP1 following radical prostatectomy for prostate cancer: a cohort study and meta-analysis

AIMS

Zinc-alpha 2-glycoprotein (AZGP1) is a promising tissue biomarker to predict outcomes in men undergoing treatment for localised prostate cancer (PCa). We aimed to examine the association between AZGP1 expression and the endpoints: risk of biochemical failure (BF), initiating castration-based treatment, developing castration-resistant PCa (CRPC) and PCa-specific mortality following radical prostatectomy (RP).

METHODS

The study included a prospective cohort of 302 patients who underwent RP for PCa from 2002 to 2005. AZGP1 expression was analysed using immunohistochemistry on tissue microarray RP specimens and was scored semiquantitively as low or high expression. Risk of all endpoints was analysed using stratified cumulative incidences and cause-specific Cox regression, and validated with receiver operating curves, calibration and discrimination in competing-risk analyses. A meta-analysis was performed including previous studies investigating AZGP1 expression and risk of BF following RP.

RESULTS

Median time of follow-up was 14.0 years. The cumulative incidence of all endpoints was significantly higher in patients with low AZGP1 expression compared with patients with high AZGP1 expression (p<0.001). In a multivariate analysis, low AZGP1 expression increases the risk of BF (HR 2.7; 95% CI 1.9 to 3.8; p<0.0001), castration-based treatment (HR 2.2; 95% CI 1.2 to 4.2; p=0.01) and CRPC (HR 2.3; 95% CI 1.1 to 5.0; p=0.03). Validation showed a low risk of prediction error and a high model performance for all endpoints. In a meta-analysis, low AZGP1 was associated with BF (HR 1.7; 95% CI 1.2 to 2.5).

CONCLUSIONS

Low AZGP1 expression is associated with the risk of aggressive time-dependent outcomes in men undergoing RP for localised PCa.

Approaches to urinary detection of prostate cancer

Background:

Prostate cancer is the most common cancer in American men that ranges from low risk states amenable to active surveillance to high risk states that can be lethal especially if untreated. There is a critical need to develop relatively non-invasive and clinically useful methods for screening, detection, prognosis, disease monitoring, and prediction of treatment efficacy. In this review, we focus on important advances as well as future efforts needed to drive clinical innovation in this area of urine biomarker research for prostate cancer detection and prognostication.

Methods:

We provide a review of current literature on urinary biomarkers for prostate cancer. We evaluate the strengths and limitations of a variety of approaches that vary in sampling strategies and targets measured; discuss reported urine tests for prostate cancer with respect to their technical, analytical, and clinical parameters; and provide our perspectives on critical considerations in approaches to developing a urine-based test for prostate cancer.

Results:

There has been an extensive history of exploring urine as a source of biomarkers for prostate cancer that has resulted in a variety of urine tests that are in current clinical use. Importantly, at least three tests have demonstrated high sensitivity (~90%) and negative predictive value (~95%) for clinically significant tumors; however, there has not been widespread adoption of these tests.

Conclusions:

Conceptual and methodological advances in the field will help to drive the development of novel urinary tests that in turn may lead to a shift in the clinical paradigm for prostate cancer diagnosis and management.

Estudio proteómico 2DE-DIGE en plasma sanguíneo de pacientes en etapa infantil con leucemia linfoblástica aguda

En Colombia, durante la última década la leucemia linfoblástica aguda (LLA) ha sido el cáncer con mayor incidencia, siendo más del 40% de las muertes por cáncer en menores de edad atribuidas a esta enfermedad. Entre los factores que influyen en estas cifras, el diagnóstico tardío es tal vez el factor más sensible que afecta de manera negativa el éxito del tratamiento. Esta investigación se centró en el estudio del proteoma plasmático de niños colombianos diagnosticados con LLA tipo B, dada su alta incidencia, en comparación con controles en la búsqueda de proteínas que podrían tener potencialidad a ser clasificadas como biomarcadores de diagnóstico. Ahora bien, en vista de los avances en las herramientas proteómicas y de espectrometría de masas y sabiendo que son una alternativa para abordar la complejidad molecular de enfermedades como el cáncer, utilizamos una aproximación proteómica basada en una separación por electroforesis bidimensional diferencial (2DE-DIGE) con posterior separación por cromatografía líquida acoplada a espectrometría de masas en tándem. Se encontraron 8 proteínas con expresión diferencial en plasma de pacientes con LLA-B, entre las cuales resaltan la serotransferrina, la Alfa-1-antitripsina, la haptoglobina, la α2-glicoproteína de zinc y la complemento C3.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

Prostate cancer is one of the most commonly diagnosed malignancy and the fifth leading cause of cancer mortality in men. Despite the broad use of prostate-specific antigen test that resulted in an increase in number of diagnosed cases, disease management needs to be improved. Proteomic biomarkers alone and or in combination with clinical and pathological risk calculators are expected to improve on decreasing the unnecessary biopsies, stratify low risk patients, and predict response to treatment. To this end, significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment. In the era of “big data” and “personalized medicine” proteomics-based biomarkers hold great promise to provide clinically applicable tools, as proteins regulate all biological functions, and integrate genomic information with the environmental impact. In this review article, we aim to provide a critical assessment of the current proteomics-based biomarkers for prostate cancer and their actual clinical applicability. For that purpose, a systematic review of the literature published within the last 10 years was performed using the Web of Science Database. We specifically discuss the potential and prospects of use for diagnostic, prognostic and predictive proteomics-based biomarkers, including both body fluid- and tissue-based markers.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

Urinary biomarkers of prostate cancer

The development of more specific biomarkers for prostate cancer and/or high-risk prostate cancer is necessary, because the prostate-specific antigen test lacks specificity for the detection of prostate cancer and can lead to unnecessary prostate biopsies. Urine is a promising source for the development of new biomarkers of prostate cancer. Biomarkers derived from prostate cancer cells are released into prostatic fluids and then into urine. Urine after manipulation of the prostate is enriched with prostate cancer biomarkers, which include prostate cancer cells, DNAs, RNAs, proteins and other small molecules. The urinary prostate cancer antigen 3 test is the first Food and Drug Administration-approved RNA-based urinary marker, and it helps in the detection of prostate cancer on repeat biopsy. The SelectMDx test is based on messenger RNA detection of DLX1 and HOXC6 in urine after prostate massage, and helps in the detection of high-risk prostate cancer on prostate biopsy. Exosomes are extracellular vesicles with a diameter of 30-200 nm that are secreted from various types of cells. Urinary prostate cancer-derived exosomes also contain RNAs and proteins specific for prostate cancer (e.g. PCA3 and TMPRSS2-ERG), and could be promising sources of novel biomarker discovery. The ExoDx Prostate test is a commercially available test based on the detection of three genes (PCA3, ERG and SPDEF) in urinary exosomes. Advancement of comprehensive analysis (microarray, mass spectrometry and next-generation sequencing) has resulted in the discovery of several urinary biomarkers. Non-invasive urinary markers can help in the decision to carry out prostate biopsy or in the design of a therapeutic strategy.

Hyaluronic acid and hyaluronidase as possible novel urine biomarkers for the diagnosis of prostate cancer

The goal of the study is to examine the possible use of HA (hyaluronic acid) and HAase (hyaluronidase) as novel urine biomarkers for the early diagnosis for prostate cancer (Pca). After a prostatic massage, the urine of 118 high-risk patients for Pca was collected, and the patients were submitted to ultrasound-guided transrectal biopsy. HA and HAase were detected and analyzed with Enzyme-Linked Immunosorbent Assay, and a statistical analysis of the urine levels of the two biomarkers according to the histology results was performed. HAase and HA were independently associated with Pca, and both HAase and HA showed significant predictive ability for prostate cancer. With an optimal cut-off point of 183.71 HAase had 70% sensitivity maintaining at the same time a 55.2% specificity, while the optimal cut-off point for HA was 50.13 with 65% sensitivity and 53.9% specificity. Patients with HAase more than 183.71 ng/ml had 3.67 times greater likelihood for prostate cancer and Patients with HA more than 50.13 ng/ml had 2.31 times greater likelihood for prostate cancer. The need of novel biomarkers that will improve the efficacy of PSA is urgent. HAase and HA showed significant predictive ability for prostate cancer and were independently associated with Pca, and greater levels were associated with greater odds for prostate cancer. To Our Knowledge, this is the first study referring to the detection of HAase and HA as potential urine biomarkers for the early diagnosis of Pca.

Hyaluronic acid and hyaluronidase as possible novel urine biomarkers for the diagnosis of prostate cancer

The goal of the study is to examine the possible use of HA (hyaluronic acid) and HAase (hyaluronidase) as novel urine biomarkers for the early diagnosis for prostate cancer (Pca). After a prostatic massage, the urine of 118 high-risk patients for Pca was collected, and the patients were submitted to ultrasound-guided transrectal biopsy. HA and HAase were detected and analyzed with Enzyme-Linked Immunosorbent Assay, and a statistical analysis of the urine levels of the two biomarkers according to the histology results was performed. HAase and HA were independently associated with Pca, and both HAase and HA showed significant predictive ability for prostate cancer. With an optimal cut-off point of 183.71 HAase had 70% sensitivity maintaining at the same time a 55.2% specificity, while the optimal cut-off point for HA was 50.13 with 65% sensitivity and 53.9% specificity. Patients with HAase more than 183.71 ng/ml had 3.67 times greater likelihood for prostate cancer and Patients with HA more than 50.13 ng/ml had 2.31 times greater likelihood for prostate cancer. The need of novel biomarkers that will improve the efficacy of PSA is urgent. HAase and HA showed significant predictive ability for prostate cancer and were independently associated with Pca, and greater levels were associated with greater odds for prostate cancer. To Our Knowledge, this is the first study referring to the detection of HAase and HA as potential urine biomarkers for the early diagnosis of Pca.

Peroxiredoxin-2 and zinc-alpha-2-glycoprotein as potentially combined novel salivary biomarkers for early detection of oral squamous cell carcinoma using proteomic approaches

No effective screening method is available for oral squamous cell carcinoma (OSCC) that is recognized to influence by environmental factors as well as human papillomavirus (HPV) and Epstein-Barr virus (EBV). Therefore, we sought to identify salivary biomarkers for screening of OSCC with or without HPV and/or EBV infection. Saliva, lesion and oral exfoliated cells were collected from OSCC patients and cancer-free controls (CFCs) and grouped depending on their HPV- and EBV-infection status. Salivary protein was precipitated and subjected to 2-dimensional gel electrophoresis. Differential expression of proteins was identified by mass spectrometry and validated by Western blotting. Distinctive expression patterns of salivary proteins were detected in OSCC as compared with CFCs. Levels of peroxiredoxin-2 (PRDX-2) and zinc-alpha-2-glycoprotein (ZAG) were significantly up-regulated in OSCC cases (p<0.001) relative to CFCs. Similarly, these proteins were also up-regulated in lesion cells compared with oral exfoliated cells (p<0.001). However, the expression patterns of these proteins were not significantly influenced by patient histories (risk factors). In combination, these proteins yielded the highest discriminatory power (AUC=0.999), sensitivity (100%), and specificity (98.77%) in distinguishing the early stages of OSCC. The detection of PRDX-2 combining with ZAG protein could potentially be used as salivary biomarkers for early screening of OSCC.

SIGNIFICANCE

Our findings demonstrate a useful of combined detection of PRDX-2 and ZAG as a salivary biomarker for the early detection of OSCC.

Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions-in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens.Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281-93. ©2017 AACR.

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Recent progress in urinary proteome analysis for prostate cancer diagnosis and management

Prostate cancer (PCa) is fifth leading cause of cancer-associated deaths in men worldwide. Although the application of the serum prostate-specific antigen (PSA) screening test resulted in an increase in the PCa diagnosed cases, it demonstrated a negligible benefit regarding the associated mortality. Treatment options vary, with active surveillance to be preferable for patients with low-risk PCa and therapy of advanced castration-resistant PCa to rely on α-emitters and cytotoxic chemotherapy. Although recent developments have led to the approval of novel drugs for the treatment of castration-resistant PCa, the optimal sequence and timing of medication have not been yet determined. New screening modalities could improve the discriminatory accuracy between tumors with favorable clinical prognosis. Implementation of proteomic-based biomarkers appears to be a promising improvement, which could enable a more accurate diagnosis, guide treatment and improve patient outcome. Reviewed here are urinary proteome-based approaches for detection of PCa and patient management.

Current biomarkers for diagnosing of prostate cancer

Prostate cancer (PCa) is mostly detected by prostate-specific antigen (PSA) as one of the most widely used tumor markers. But PSA is limited with its low specificity. The prostate health index (phi) can improve specificity over percent free and total PSA and correlates with aggressive cancer. The urinary PCA3 also shows its utility to detect PCa but its correlation with aggressiveness and the low sensitivity at high values are limitations. While the detection of alterations of the androgen-regulated TMPRSS2 and ETS transcription factor genes in tissue of ˜50% of all PCa patients was one research milestone, the urinary assay should only be used in combination with PCA3. Both US FDA-approved markers phi and PCA3 perform equally.

iTRAQ-Based Quantitative Proteomic Analysis Identified HSC71 as a Novel Serum Biomarker for Renal Cell Carcinoma

Renal cell carcinoma (RCC) is one of the most lethal urologic cancers and about 80% of RCC are of the clear-cell type (ccRCC). However, there are no serum biomarkers for the accurate diagnosis of RCC. In this study, we performed a quantitative proteomic analysis on serum samples from ccRCC patients and control group by using isobaric tag for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to access differentially expressed proteins. Overall, 16 proteins were significantly upregulated (ratio > 1.5) and 14 proteins were significantly downregulated (ratio < 0.67) in early-stage ccRCC compared to control group. HSC71 was selected and subsequently validated by Western blot in six independent sets of patients. ELISA subsequently confirmed HSC71 as a potential serum biomarker for distinguishing RCC from benign urologic disease with an operating characteristic curve (ROC) area under the curve (AUC) of 0.86 (95% confidence interval (CI), 0.76~0.96), achieving sensitivity of 87% (95% CI 69%~96%) at a specificity of 80% (95% CI 61~92%) with a threshold of 15 ng/mL. iTRAQ-based quantitative proteomic analysis led to identification of serum HSC71 as a novel serum biomarker of RCC, particularly useful in early diagnosis of ccRCC.

Prostate-specific antigen and other serum and urine markers in prostate cancer

Prostate-specific antigen (PSA) is one of the most widely used tumor markers, and strongly correlates with the risk of harboring from prostate cancer (PCa). This risk is visible already several years in advance but PSA has severe limitations for PCa detection with its low specificity and low negative predictive value. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved Prostate Health Index (phi) shows improved specificity over percent free and total PSA. Other serum kallikreins or sarcosine in serum or urine show more diverging data. In urine, the FDA-approved prostate cancer gene 3 (PCA3) has also proven its utility in the detection and management of early PCa. However, some aspects on its correlation with aggressiveness and the low sensitivity at very high values have to be re-examined. The detection of a fusion of the androgen regulated TMPRSS2 gene with the ERG oncogene (from the ETS family), which acts as transcription factor gene, in tissue of ~50% of all PCa patients was one milestone in PCa research. When combining the urinary assays for TMPRSS2:ERG and PCA3, an improved accuracy for PCa detection is visible. PCA3 and phi as the best available PCa biomarkers show an equal performance in direct comparisons.

Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics

Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies.

Proteomic and cytokine plasma biomarkers for predicting progression from colorectal adenoma to carcinoma in human patients

In the present study, we screened proteomic and cytokine biomarkers between patients with adenomatous polyps and colorectal cancer (CRC) in order to improve our understanding of the molecular mechanisms behind turmorigenesis and tumor progression in CRC. To this end, we performed comparative proteomic analysis of plasma proteins using a combination of 2DE and MS as well as profiled differentially regulated cytokines and chemokines by multiplex bead analysis. Proteomic analysis identified 11 upregulated and 13 downregulated plasma proteins showing significantly different regulation patterns with diagnostic potential for predicting progression from adenoma to carcinoma. Some of these proteins have not previously been implicated in CRC, including upregulated leucine-rich α-2-glycoprotein, hemoglobin subunit β, Ig α-2 chain C region, and complement factor B as well as downregulated afamin, zinc-α-2-glycoprotein, vitronectin, and α-1-antichymotrypsin. In addition, plasma levels of three cytokines/chemokines, including interleukin-8, interferon gamma-induced protein 10, and tumor necrosis factor α, were remarkably elevated in patients with CRC compared to those with adenomatous polyps. Although further clinical validation is required, these proteins and cytokines can be established as novel biomarkers for CRC and/or its progression from colon adenoma.

The present and future of prostate cancer urine biomarkers

In order to successfully cure patients with prostate cancer (PCa), it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field.

The role of proteomics in prostate cancer research: biomarker discovery and validation

PURPOSE

Prostate Cancer (PCa) represents the second most frequent type of tumor in men worldwide. Incidence increases with patient age and represents the most important risk factor. PCa is mostly characterized by indolence, however in a small percentage of cases (3%) the disease progresses to a metastatic state. To date, the most important issue concerning PCa research is the difficulty in distinguishing indolent from aggressive disease. This problem frequently results in low-grade PCa patient overtreatment and, in parallel; an effective treatment for distant and aggressive disease is not yet available.

RESULT

Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PCa patients. Markers more specific and sensitive than PSA are needed for PCa diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PCa tailored therapy. Several possible PCa biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.

CONCLUSIONS

This review aims to discuss the recent advances in PCa proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.