Maria Frantzi

Profilin 1 is a Potential Biomarker for Bladder Cancer Aggressiveness

Of the most important clinical needs for bladder cancer (BC) management is the identification of biomarkers for disease aggressiveness. Urine is a “gold mine” for biomarker discovery, nevertheless, with multiple proteins being in low amounts, urine proteomics becomes challenging. In the present study we applied a fractionation strategy of urinary proteins based on the use of immobilized metal affinity chromatography for the discovery of biomarkers for aggressive BC. Urine samples from patients with non invasive (two pools) and invasive (two pools) BC were subjected to immobilized metal affinity chromatography fractionation and eluted proteins analyzed by 1D-SDS-PAGE, band excision and liquid chromatography tandem MS. Among the identified proteins, multiple corresponded to proteins with affinity for metals and/or reported to be phosphorylated and included proteins with demonstrated association with BC such as MMP9, fibrinogen forms, and clusterin. In agreement to the immobilized metal affinity chromatography results, aminopeptidase N, profilin 1, and myeloblastin were further found to be differentially expressed in urine from patients with invasive compared with non invasive BC and benign controls, by Western blot or Elisa analysis, nevertheless exhibiting high interindividual variability. By tissue microarray analysis, profilin 1 was found to have a marked decrease of expression in the epithelial cells of the invasive (T2+) versus high risk non invasive (T1G3) tumors with occasional expression in stroma; importantly, this pattern strongly correlated with poor prognosis and increased mortality. The functional relevance of profilin 1 was investigated in the T24 BC cells where blockage of the protein by the use of antibodies resulted in decreased cell motility with concomitant decrease in actin polymerization. Collectively, our study involves the application of a fractionation method of urinary proteins and as one main result of this analysis reveals the association of profilin 1 with BC paving the way for its further investigation in BC stratification.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic–based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.

Developing proteomic biomarkers for bladder cancer: towards clinical application

Clinical use of proteomic biomarkers has the potential to substantially improve the outcomes of patients with bladder cancer. An unmet clinical need evidently exists for noninvasive biomarkers, which might enable improvements in both the diagnosis and prognosis of patients with bladder cancer, as well as improved monitoring of patients for the presence of recurrence. Urine is considered the optimal noninvasive source of proteomic biomarkers in patients with bladder cancer. Currently, a number of single-protein biomarkers have been detected in urine and tissue using a variety of proteomic techniques, each having specific conceptual considerations and technical implications. Promising preclinical data are available for several of these proteins; however, the combination of single urinary proteins into multimarker panels might better encompass the molecular heterogeneity of bladder cancer within this patient population, and prove more effective in clinical use.

Biomarkers for bladder cancer aggressiveness.

Purpose of reviewBladder cancer is associated with high recurrence and mortality rates. Development of accurate surveillance tests to evaluate disease aggressiveness and for prognosis of disease recurrence and progression is a major clinical need. At the molecular level bladder cancer displays a vast heterogeneity as reflected by the presence of multiple potential biomarkers associated with various disease phenotypes. The scope of this review is to briefly summarize the latest findings on biomarkers potentially beneficial in disease stratification based on aggressiveness and prognosis. Recent findingsMultiple potential biomarkers for bladder cancer have been identified corresponding to chromosome, DNA, and epigenetic alterations, as well as changes in RNA, miRNAs, and protein expression levels and modifications. We summarize some of the main biomarker findings reported in the past year that are considered to be potentially correlated to disease aggressiveness. A comparison to existing latest evidence from the classical US Food and Drug Administration-approved bladder cancer detection markers is made. SummaryPotential biomarkers detected noninvasively in urine specimens, as well as in excised tissue specimens following initial treatment, are briefly reported. The prognostic information provided may be significant, as multiple markers by now have been found to correlate with disease outcome. However, the studies presented were in general either too small, and/or the performance of the single biomarkers was moderate. The information presently available suggests that single biomarkers may be insufficient for effective monitoring and patient management. A concerted effort to establish panels of biomarkers based on the ample existing knowledge, and validate them in proper clinical trials is urgently needed.

Discovery and validation of urinary biomarkers for detection of renal cell carcinoma.

INTRODUCTION Renal cell carcinoma (RCC) is often accompanied by non-specific symptoms. The increase of incidentally discovered small renal masses also presents a diagnostic dilemma. This study investigates whether RCC-specific peptides with diagnostic potential can be detected in urine and whether a combination of such peptides could form a urinary screening tool. MATERIALS AND METHODS For the discovery of RCC-specific biomarkers, we have employed CE-MS to analyze urine samples from patients with RCC (N=40) compared to non-diseased controls (N=68). RESULTS AND DISCUSSION 86 peptides were found to be specifically associated to RCC, of which sequence could be obtained for 40. A classifier based on these peptides was evaluated in an independent set of 76 samples, resulting in 80% sensitivity and 87% specificity. The specificity of the marker panel was further validated in a historical dataset of 1077 samples including age-matched controls (N=218), patients with related cancer types and renal diseases (N=859). In silico protease prediction based on the cleavage sites of differentially excreted peptides, suggested modified activity of certain proteases including cathepsins, ADAMTS and kallikreins some of which were previously found to be associated to RCC. CONCLUSIONS RCC can be detected with high accuracy based on specific urinary peptides. BIOLOGICAL SIGNIFICANCE Clear cell renal cell carcinoma (RCC) has the highest incidence among the renal malignancies, often presenting non-specific or no symptoms at all. Moreover, with no diagnostic marker being available so far, almost 30% of the patients are diagnosed with metastatic disease and 30-40% of the patients initially diagnosed with localized tumor relapse. These facts introduce the clinical need of early diagnosis. This study is focused on the investigation of a marker model based on urinary peptides, as a tool for the detection of RCC in selected patients at risk. Upon evaluation of the marker model in an independent blinded set of 76 samples, 80% sensitivity and 87% specificity were reported. An additional dataset of 1077 samples was subsequently employed for further evaluation of the specificity of the classifier.

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well‐characterized biomarkers appears appropriate, providing a more robust and sensitive MS‐based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE‐MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE‐MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE‐MS in the management of genitourinary cancers, especially bladder cancer. CE‐MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle‐invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.

Development and validation of urine-based peptide biomarker panels for detecting bladder cancer in a multi-center study

Purpose: Urothelial bladder cancer presents high recurrence rates, mandating continuous monitoring via invasive cystoscopy. The development of noninvasive tests for disease diagnosis and surveillance remains an unmet clinical need. In this study, validation of two urine-based biomarker panels for detecting primary and recurrent urothelial bladder cancer was conducted. Experimental Design: Two studies (total n = 1,357) were performed for detecting primary (n = 721) and relapsed urothelial bladder cancer (n = 636). Cystoscopy was applied for detecting urothelial bladder cancer, while patients negative for recurrence had follow-up for at least one year to exclude presence of an undetected tumor at the time of sampling. Capillary electrophoresis coupled to mass spectrometry (CE-MS) was employed for the identification of urinary peptide biomarkers. The candidate urine–based peptide biomarker panels were derived from nested cross-sectional studies in primary (n = 451) and recurrent (n = 425) urothelial bladder cancer. Results: Two biomarker panels were developed on the basis of 116 and 106 peptide biomarkers using support vector machine algorithms. Validation of the urine-based biomarker panels in independent validation sets, resulted in AUC values of 0.87 and 0.75 for detecting primary (n = 270) and recurrent urothelial bladder cancer (n = 211), respectively. At the optimal threshold, the classifier for detecting primary urothelial bladder cancer exhibited 91% sensitivity and 68% specificity, while the classifier for recurrence demonstrated 87% sensitivity and 51% specificity. Particularly for patients undergoing surveillance, improved performance was achieved when combining the urine-based panel with cytology (AUC = 0.87). Conclusions: The developed urine-based peptide biomarker panel for detecting primary urothelial bladder cancer exhibits good performance. Combination of the urine-based panel and cytology resulted in improved performance for detecting disease recurrence. Clin Cancer Res; 22(16); 4077–86. ©2016 AACR.

IMAC fractionation in combination with LC–MS reveals H2B and NIF-1 peptides as potential bladder cancer biomarkers

Improvement in bladder cancer (BC) management requires more effective diagnosis and prognosis of disease recurrence and progression. Urinary biomarkers attract special interest because of the noninvasive means of urine collection. Proteomic analysis of urine entails the adoption of a fractionation methodology to reduce sample complexity. In this study, we applied immobilized metal affinity chromatography in combination with high-resolution LC-MS/MS for the discovery of native urinary peptides potentially associated with BC aggressiveness. This approach was employed toward urine samples from patients with invasive BC, noninvasive BC, and benign urogenital diseases. A total of 1845 peptides were identified, corresponding to a total of 638 precursor proteins. Specific enrichment for proteins involved in nucleosome assembly and for zinc-finger transcription factors was observed. The differential expression of two candidate biomarkers, histone H2B and NIF-1 (zinc finger 335) in BC, was verified in independent sets of urine samples by ELISA and by immunohistochemical analysis of BC tissue. The results collectively support changes in the expression of both of these proteins with tumor progression, suggesting their potential role as markers for discriminating BC stages. In addition, the data indicate a possible involvement of NIF-1 in BC progression, likely as a suppressor and through interactions with Sox9 and HoxA1.

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.

Clinical Proteomics for Precision Medicine: The Bladder Cancer Case

Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of ‐omics‐based approaches. Proteomics attract high interest, as proteins reflect a “real‐time” dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention, and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggest that earlier and more efficient intervention, continuous monitoring, and the development of alternative therapies could be accomplished by applying proteomics‐guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics‐guided personalized patient management.