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

Uncovering New Biomarkers for Prostate Cancer Through Proteomic and Network Analysis

BACKGROUND

Prostate cancer (PCa), is the second most prevalent solid tumor among men worldwide (7.3%), and the leading non-skin cancer in USA where it represents 14.9% of all new cancer cases diagnosed in 2024. This multifactorial disease exhibits substantial variation in incidence and mortality across different ethnic groups and geographic regions. Although prostate-specific antigen (PSA) remains widely used as a biomarker for PCa, its limitations reduce its effectiveness for accurate detection. Consequently, finding molecules that can either complement PSA and other biomarkers is a major goal in PCa research.

METHODS

Urine samples were collected from healthy donors (n = 5) and patients with low- and high-risk PCa (4 and 7 subjects, respectively) and were analyzed using proteomic data-derived systems and biology approaches. The most promising proteins were further investigated by means of The Cancer Genome Atlas (TCGA) database to assess their associations with clinical and histopathological characteristics in a larger in silico patient population.

RESULTS

By evaluating the variations in the urinary proteome as a mirror of the changes occurring in prostate tumor tissue, components of complement and coagulation cascades and glutathione metabolism emerged as hallmarks of low- and high-risk PCa patients, respectively. Moreover, our integrated approach highlighted new potential biomarkers, including CPM, KRT8, ITIH2, and RCN1.

CONCLUSIONS

The good overlap of our results with what is already reported in the literature supports the new findings in the perspective of improving the knowledge on PCa. Furthermore, they increase the panel of biomarkers that could enhance PCa management. Of course, further investigations on larger patient cohorts are required.

Unleashing the power of urine‑based biomarkers in diagnosis, prognosis and monitoring of bladder cancer (Review)

Bladder cancer (BCa) is a prevalent malignant neoplasm of the urinary tract with high incidence rate, frequent recurrence and rapid disease progression. Conventional approaches for diagnosing, prognosticating and monitoring BCa often rely on invasive procedures such as cystoscopy and tissue biopsy, which are associated with high costs and low patient compliance for follow‑up. Liquid biopsies have advantages, such as being non‑invasive, real‑time, and reproducible, in obtaining diverse biomarkers derived from cellular, molecular, proteomic and genetic signatures in urine or plasma samples. Although plasma‑based biomarkers have been clinically validated, urine provides greater specificity for directly assessing biological materials from urological sources. The present review summarizes advancements and current limitations in urinary protein, genetic and epigenetic biomarkers for disease progression and treatment response of BC, compares performance and application scenarios of urine and blood biomarkers and explores how urinary biomarkers may serve as an alternative or complementary tool to traditional diagnostic methods. The integration of urine‑based or plasma‑based biomarkers into existing diagnostic workflows offers promising avenues for improving accuracy and efficiency of diagnosis in the management of BCa. Notably, the emergence of synthetic biomarkers and urine metabolites, combined with artificial intelligence or bioinformatic technologies, has promise in the screening of potential targets. Continued research and validation efforts are needed to translate these findings into routine clinical practice, ultimately improving patient outcomes and decreasing the burden of BCa.

Comparative Serum Proteome Profiling of Canine Benign Prostatic Hyperplasia before and after Castration

BPH is the most prevalent prostatic condition in aging dogs. Nevertheless, clinical diagnosis and management remain inconsistent. This study employed in-solution digestion coupled with nano-liquid chromatography tandem mass spectrometry to assess serum proteome profiling of dogs with BPH and those dogs after castration. Male dogs were divided into two groups; control and BPH groups. In the BPH group, each dog was evaluated at two time points: Day 0 (BF subgroup) and Day 30 after castration (AT subgroup). In the BF subgroup, three proteins were significantly upregulated and associated with dihydrotestosterone: solute carrier family 5 member 5, tyrosine-protein kinase, and FRAT regulator of WNT signaling pathway 1. Additionally, the overexpression of polymeric immunoglobulin receptors in the BF subgroup hints at its potential as a novel protein linked to the BPH development process. Conversely, alpha-1-B glycoprotein (A1BG) displayed significant downregulation in the BF subgroup, suggesting A1BG's potential as a predictive protein for canine BPH. Finasteride was associated with increased proteins in the AT subgroup, including apolipoprotein C-I, apolipoprotein E, apolipoprotein A-II, TAO kinase 1, DnaJ homolog subfamily C member 16, PH domain and leucine-rich repeat protein phosphatase 1, neuregulin 1, and pseudopodium enriched atypical kinase 1. In conclusion, this pilot study highlighted alterations in various serum proteins in canine BPH, reflecting different pathological changes occurring in this condition. These proteins could be a source of potential non-invasive biomarkers for diagnosing this disease.

Several Potential Serum Proteomic Biomarkers for Diagnosis of Osteoarticular Tuberculosis Based on Mass Spectrometry

BACKGROUND

Osteoarticular tuberculosis is one of the extrapulmonary tuberculosis (EPTB) diseases, which is mainly caused by infection of Mycobacterium tuberculosis (MTB) in bone and joints. The limitation of current clinical test methods is leading to a high misdiagnosis rate and affecting the treatment and prognosis. This study aims to search serum biomarkers that can assist in the diagnosis of osteoarticular tuberculosis.

METHODS

Proteomics can serve as an important method in the discovery of disease biomarkers. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to analyze proteins in 90 serum samples, which were collected from June 2020 to December 2021, then evaluated by statistical analysis to screen potential biomarkers. After that, potential biomarkers were validated by ELISA and diagnostic models were also established for observation of multi-index diagnostic efficacy.

RESULTS

118 differential expressed proteins (DEPs) were obtained in serum after statistical analysis. After the diagnostic efficacy evaluation and clinical verification, inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2), complement factor H-related protein 2 (CFHR2), complement factor H-related protein 3 (CFHR3) and complement factor H-related protein 5 (CFHR5) were found as potential biomarkers, with 0.7167 (95%CI: 0.5846-0.8487), 0.8600 (95%CI: 0.7701-0.9499), 0.8150 (95%CI: 0.6998-0.9302), and 0.9978 (95%CI: 0.9918-1.0040) AUC value, respectively. The remaining DEPs except CFHR5 were constructed as diagnostic models, the diagnostic model contained CFHR2 and CFHR3 had good diagnostic efficacy with 0.942 (95%CI: 0.872-0.980) AUC value compared to other models.

CONCLUSION

This study provides a reference for the discovery of serum protein markers for osteoarticular tuberculosis diagnosis, and the screened DEPs can also provide directions for subsequent pathogenesis research.

A peptide-centric approach to analyse quantitative proteomics data- an application to prostate cancer biomarker discovery

Bottom-up proteomics is a popular approach in molecular biomarker research. However, protein analysts have realized the limitations of protein-based approaches for identifying and quantifying proteins in complex samples, such as the identification of peptides sequences shared by multiple proteins and the difficulty in identifying modified peptides. Thus, there are many exciting opportunities to improve analysis methods. Here, an alternative method focused on peptide analysis is proposed as a complement to the conventional proteomics data analysis. To investigate this hypothesis, a peptide-centric approach was applied to reanalyse a urine proteome dataset of samples from prostate cancer patients and controls. The results were compared with the conventional protein-centric approach. The relevant proteins/peptides to discriminate the groups were detected based on two approaches, p-value and VIP values obtained by a PLS-DA model. A comparison of the two strategies revealed high inconsistency between protein and peptide information and greater involvement of peptides in key PCa processes. This peptide analysis unveiled discriminative features that are lost when proteins are analyzed as homogeneous entities. This type of analysis is innovative in PCa and integrated with the widely used protein-centric approach might provide a more comprehensive view of this disease and revolutionize biomarker discovery. SIGNIFICANCE: In this study, the application of a protein and peptide-centric approaches to reanalyse a urine proteome dataset from prostate cancer (PCa) patients and controls showed that many relevant proteins/peptides are missed by the conservative nature of p-value in statistical tests, therefore, the inclusion of variable selection methods in the analysis of the dataset reported in this work is fruitful. Comparison of protein- and peptide-based approaches revealed a high inconsistency between protein and peptide information and a greater involvement of peptides in key PCa processes. These results provide a new perspective to analyse proteomics data and detect relevant targets based on the integration of peptide and protein information. This data integration allows to unravel discriminative features that normally go unnoticed, to have a more comprehensive view of the disease pathophysiology and to open new avenues for the discovery of biomarkers.

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.

Identification of Urine Biomarkers to Improve Eligibility for Prostate Biopsy and Detect High-Grade Prostate Cancer

PCa screening is based on the measurements of the serum prostate specific antigen (PSA) to select men with higher risks for tumors and, thus, eligible for prostate biopsy. However, PSA testing has a low specificity, leading to unnecessary biopsies in 50-75% of cases. Therefore, more specific screening opportunities are needed to reduce the number of biopsies performed on healthy men and patients with indolent tumors. Urine samples from 45 patients with elevated PSA were collected prior to prostate biopsy, a mass spectrometry (MS) screening was performed to identify novel biomarkers and the best candidates were validated by ELISA. The urine quantification of PEDF, HPX, CD99, CANX, FCER2, HRNR, and KRT13 showed superior performance compared to PSA. Additionally, the combination of two biomarkers and patient age resulted in an AUC of 0.8196 (PSA = 0.6020) and 0.7801 (PSA = 0.5690) in detecting healthy men and high-grade PCa, respectively. In this study, we identified and validated novel urine biomarkers for the screening of PCa, showing that an upfront urine test, based on quantitative biomarkers and patient age, is a feasible method to reduce the number of unnecessary prostate biopsies and detect both healthy men and clinically significant PCa.