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, suggests 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

Urinary CE-MS peptide marker pattern for detection of solid tumors

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features

Omics derived biomarkers and novel drug targets for improved intervention in advanced prostate cancer

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies, and the fifth leading cause of cancer related mortality in men. For advanced PCa, radical prostatectomy, radiotherapy, and/or long-term androgen deprivation therapy are the recommended treatment options. However, subsequent progression to metastatic disease after initial therapy results in low 5-year survival rates (29%). Omics technologies enable the acquisition of high-resolution large datasets that can provide insights into molecular mechanisms underlying PCa pathology. For the purpose of this article, a systematic literature search was conducted through the Web of Science Database to critically evaluate recent omics-driven studies that were performed towards: (a) Biomarker development and (b) characterization of novel molecular-based therapeutic targets. The results indicate that multiple omics-based biomarkers with prognostic and predictive value have been validated in the context of PCa, with several of those being also available for commercial use. At the same time, omics-driven potential drug targets have been investigated in pre-clinical settings and even in clinical trials, holding the promise for improved clinical management of advanced PCa, as part of personalized medicine pipelines

Integrative analysis of extracellular and intracellular bladder cancer cell line proteome with transcriptome: improving coverage and validity of -omics findings

Characterization of disease-associated proteins improves our understanding of disease pathophysiology. Obtaining a comprehensive coverage of the proteome is challenging, mainly due to limited statistical power and an inability to verify hundreds of putative biomarkers. In an effort to address these issues, we investigated the value of parallel analysis of compartment-specific proteomes with an assessment of findings by cross-strategy and cross-omics (proteomics-transcriptomics) agreement. The validity of the individual datasets and of a “verified” dataset based on crossstrategy/omics agreement was defined following their comparison with published literature. The proteomic analysis of the cell extract, Endoplasmic Reticulum/Golgi apparatus and conditioned medium of T24 vs. its metastatic subclone T24M bladder cancer cells allowed the identification of 253, 217 and 256 significant changes, respectively. Integration of these findings with transcriptomics resulted in 253 “verified” proteins based on the agreement of at least 2 strategies. This approach revealed findings of higher validity, as supported by a higher level of agreement in the literature data than those of individual datasets. As an example, the coverage and shortlisting of targets in the IL-8 signalling pathway are discussed. Collectively, an integrative analysis appears a safer way to evaluate -omics datasets and ultimately generate models from valid observations

Retrospective Analysis of Patients With Prostate Cancer Initiating GnRH Agonists/Antagonists Therapy Using a German Claims Database: Epidemiological and Patient Outcomes

Objective: The objective of this study was to obtain real-world information on gonadotropin-releasing hormone agonist/antagonist (GnRHa) therapy in patients with advanced prostate cancer (PCa).Materials and methods: Anonymized, routine healthcare claims data from approx. 75 German statutory health insurance funds from 2010–2015 (n = 4,205,227) were analyzed. Patients had an enrolment of 1 year before GnRHa, 1 index quarter of initial GnRHa prescription and ≥2 years of follow-up.Results: In total, 2,382 patients with PCa were eligible. The most frequent index therapy was leuprolide in 56.6%. The rank order of PCa comorbidity prevalence was consistent over time (% at index and 3-years of follow-up): hypertension (71.5; 85.0), hyperlipidemia (45.2; 60.8), cardiovascular disease (CVD) (35.7; 54.1), and diabetes (28.3; 36.2). Comparing pooled therapy classes (agonists, hybrids, and antagonist), no significant differences in the incidence of CVD or diabetes were observed. For hypertension, there was a significant increase for agonists (16.4%) compared to antagonists (6.9%, p = 0.022) and leuprolide hybrid group (11.6%, p = 0.006). During the follow-up period 23.9% of all PCa patients died. There were no significant differences concerning mortality rate and discontinuation rates between the cohorts. In total, 11.2% of all patients discontinued GnRHa after first prescription; the mean time to first switch to another GnRHa therapy was 100 days earlier for hybrids than for agonists (p = 0.016).Conclusion: This comparative retrospective analysis provides real-world information about healthcare characteristics and treatment patterns, highlighting the impact of different GnRHa on clinical outcomes for patients with advanced PCa in Germany

Integrative analysis of extracellular and intracellular bladder cancer cell line proteome with transcriptome: improving coverage and validity of –omics findings

Characterization of disease-associated proteins improves our understanding of disease pathophysiology. Obtaining a comprehensive coverage of the proteome is challenging, mainly due to limited statistical power and an inability to verify hundreds of putative biomarkers. In an effort to address these issues, we investigated the value of parallel analysis of compartment-specific proteomes with an assessment of findings by cross-strategy and cross-omics (proteomics-transcriptomics) agreement. The validity of the individual datasets and of a “verified” dataset based on cross-strategy/omics agreement was defined following their comparison with published literature. The proteomic analysis of the cell extract, Endoplasmic Reticulum/Golgi apparatus and conditioned medium of T24 vs. its metastatic subclone T24M bladder cancer cells allowed the identification of 253, 217 and 256 significant changes, respectively. Integration of these findings with transcriptomics resulted in 253 “verified” proteins based on the agreement of at least 2 strategies. This approach revealed findings of higher validity, as supported by a higher level of agreement in the literature data than those of individual datasets. As an example, the coverage and shortlisting of targets in the IL-8 signalling pathway are discussed. Collectively, an integrative analysis appears a safer way to evaluate -omics datasets and ultimately generate models from valid observations

Acceptance, Prevalence and Indications for Robot-Assisted Laparoscopy - Results of a Survey Among Urologists in Germany, Austria and Switzerland

Background: Robotic-assisted laparoscopy (RAL) is being widely accepted in the field of urology as a replacement for conventional laparoscopy (CL). Nevertheless, the process of its integration in clinical routines has been rather spontaneous. Objective: To determine the prevalence of robotic systems (RS) in urological clinics in Germany, Austria and Switzerland, the acceptance of RAL among urologists as a replacement for CL and its current use for 25 different urological indications. Materials and Methods: To elucidate the practice patterns of RAL, a survey at hospitals in Germany, Austria and Switzerland was conducted. All surgically active urology departments in Germany (303), Austria (37) and Switzerland (84) received a questionnaire with questions related to the one-year period prior to the survey. Results: The response rate was 63%. Among the participants, 43% were universities, 45% were tertiary care centres, and 8% were secondary care hospitals. A total of 60 RS (Germany 35, Austria 8, Switzerland 17) were available, and the majority (68%) were operated under public ownership. The perception of RAL and the anticipated superiority of RAL significantly differed between robotic and non-robotic surgeons. For only two urologic indications were more than 50% of the procedures performed using RAL: pyeloplasty (58%) and transperitoneal radical prostatectomy (75%). On average, 35% of robotic surgeons and only 14% of non-robotic surgeons anticipated RAL superiority in some of the 25 indications. Conclusions: This survey provides a detailed insight into RAL implementation in Germany, Austria and Switzerland. RAL is currently limited to a few urological indications with a small number of high-volume robotic centres. These results might suggest that a saturation of clinics using RS has been achieved but that the existing robotic capacities are being utilized ineffectively. The possible reasons for this finding are discussed, and certain strategies to solve these problems are offered

Fibronectin 1 mRNA expression correlates with advanced disease in renal cancer

<p>Abstract</p> <p>Background</p> <p>Fibronectin 1 (<it>FN1</it>) is a glycoprotein involved in cellular adhesion and migration processes. The aim of this study was to elucidate the role of <it>FN1 </it>in development of renal cell cancer (RCC) and to determine a prognostic relevance for optimal clinical management.</p> <p>Methods</p> <p>212 renal tissue samples (109 RCC, 86 corresponding tissues from adjacent normal renal tissue and 17 oncocytomas) were collected from patients undergoing surgery for renal tumors and subjected to total RNA extraction. Detection of <it>FN1 </it>mRNA expression was performed using quantitative real time PCR, three endogenous controls, renal proximal tubular epithelial cells (RPTEC) as biological control and the ΔΔCt method for calculation of relative quantities.</p> <p>Results</p> <p>Mean tissue specific <it>FN1 </it>mRNA expression was found to be increased approximately seven fold comparing RCC and corresponding kidney control tissues (p < 0.001; ANOVA). Furthermore, tissue specific mean <it>FN1 </it>expression was increased approx. 11 fold in clear cell compared to papillary RCC (p = 9×10^-5; Wilcoxon rank sum test). Patients with advanced disease had higher <it>FN1 </it>expression when compared to organ-confined disease (p < 0.001; Wilcoxon rank sum test). Applying subgroup analysis we found a significantly higher <it>FN1 </it>mRNA expression between organ-confined and advanced disease in the papillary and not in the clear cell RCC group (p = 0.02 vs. p = 0.2; Wilcoxon rank sum test). There was an increased expression in RCC compared to oncocytoma (p = 0.016; ANOVA).</p> <p>Conclusions</p> <p>To our knowledge, this is the first study to show that <it>FN1 </it>mRNA expression is higher in RCC compared to normal renal tissue. <it>FN1 </it>mRNA expression might serve as a marker for RCC aggressiveness, indicating early systemic progression particularly for patients with papillary RCC.</p

Prognostic Value of the New Prostate Cancer International Society of Urological Pathology Grade Groups

Gleason grading is the best independent predictor for prostate cancer (PCa) progression. Recently, a new PCa grading system has been introduced by the International Society of Urological Pathology (ISUP) and is recommended by the World Health Organization (WHO). Following studies observed more accurate and simplified grade stratification of the new system. Aim of this study was to compare the prognostic value of the new grade groups compared to the former Gleason Grading and to determine whether re-definition of Gleason Pattern 4 might reduce upgrading from prostate biopsy to radical prostatectomy (RP) specimen. A cohort of men undergoing RP from 2002 to 2015 at the Hospital of Goeppingen (Goeppingen, Germany) was used for this study. In total, 339 pre-operative prostatic biopsies and corresponding RP specimens, as well as additional 203 RP specimens were re-reviewed for Grade Groups according to the ISUP. Biochemical recurrence-free survival (BFS) after surgery was used as endpoint to analyze prognostic significance. Other clinicopathological data included TNM-stage and pre-operative PSA level. Kaplan–Meier analysis revealed risk stratification of patients based on both former Gleason Grading and ISUP Grade Groups, and was statistically significant using the log-rank test (p &lt; 0.001). Both grading systems significantly correlated with TNM-stage and pre-operative PSA level (p &lt; 0.001). Higher tumor grade in RP specimen compared to corresponding pre-operative biopsy was observed in 44 and 34.5% of cases considering former Gleason Grading and ISUP Grade Groups, respectively. Both, former Gleason Grading and ISUP Grade Groups predict survival when applied on tumors in prostatic biopsies as well as RP specimens. This is the first validation study on a large representative German community-based cohort to compare the former Gleason Grading with the recently introduced ISUP Grade Groups. Our data indicate that the ISUP Grade Groups do not improve predictive value of PCa grading and might be less sensitive in deciphering tumors with 3 + 4 and 4 + 3 pattern on RP specimen. However, the Grade Group system results less frequently in an upgrading from biopsy to the corresponding RP specimens, indicating a lower risk to miss potentially aggressive tumors not represented on biopsies

Proteomics analysis of bladder cancer invasion: targeting EIF3D for therapeutic intervention

Patients with advanced bladder cancer have poor outcomes, indicating a need for more efficient therapeutic approaches. This study characterizes proteomic changes underlying bladder cancer invasion aiming for the better understanding of disease pathophysiology and identification of drug targets. High resolution liquid chromatography coupled to tandem mass spectrometry analysis of tissue specimens from patients with non-muscle invasive (NMIBC, stage pTa) and muscle invasive bladder cancer (MIBC, stages pT2+) was conducted. Comparative analysis identified 144 differentially expressed proteins between analyzed groups. These included proteins previously associated with bladder cancer and also additional novel such as PGRMC1, FUCA1, BROX and PSMD12, which were further confirmed by immunohistochemistry. Pathway and interactome analysis predicted strong activation in muscle invasive bladder cancer of pathways associated with protein synthesis e.g. eIF2 and mTOR signaling. Knock-down of eukaryotic translation initiation factor 3 subunit D (EIF3D) (overexpressed in muscle invasive disease) in metastatic T24M bladder cancer cells inhibited cell proliferation, migration, and colony formation in vitro and decreased tumor growth in xenograft models. By contrast, knocking down GTP-binding protein Rheb (which is upstream of EIF3D) recapitulated the effects of EIF3D knockdown in vitro, but not in vivo. Collectively, this study represents a comprehensive analysis of NMIBC and MIBC providing a resource for future studies. The results highlight EIF3D as a potential therapeutic target