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

Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

The extracellular matrix component perlecan/HSPG2 regulates radioresistance in prostate cancer cells

Radiotherapy of prostate cancer (PC) can lead to the acquisition of radioresistance through molecular mechanisms that involve, in part, cell adhesion-mediated signaling. To define these mechanisms, we employed a DU145 PC model to conduct a comparative mass spectrometry-based proteomic analysis of the purified integrin nexus, i.e., the cell-matrix junction where integrins bridge assembled extracellular matrix (matrisome components) to adhesion signaling complexes (adhesome components). When parental and radioresistant cells were compared, the expression of integrins was not changed, but cell radioresistance was associated with extensive matrix remodeling and changes in the complement of adhesion signaling proteins. Out of 72 proteins differentially expressed in the parental and radioresistant cells, four proteins were selected for functional validation based on their correlation with biochemical recurrence-free survival. Perlecan/heparan sulfate proteoglycan 2 (HSPG2) and lysyl-like oxidase-like 2 (LOXL2) were upregulated, while sushi repeat-containing protein X-linked (SRPX) and laminin subunit beta 3 (LAMB3) were downregulated in radioresistant DU145 cells. Knockdown of perlecan/HSPG2 sensitized radioresistant DU145 RR cells to irradiation while the sensitivity of DU145 parental cells did not change, indicating a potential role for perlecan/HSPG2 and its associated proteins in suppressing tumor radioresistance. Validation in androgen-sensitive parental and radioresistant LNCaP cells further supported perlecan/HSPG2 as a regulator of cell radiosensitivity. These findings extend our understanding of the interplay between extracellular matrix remodeling and PC radioresistance and signpost perlecan/HSPG2 as a potential therapeutic target and biomarker for PC.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Empowering peptidomics: utilizing computational tools and approaches

Bioinformatics plays a critical role in the advancement of peptidomics by providing powerful tools for data analysis, interpretation and integration. Peptidomics is concerned with the study of peptides, short chains of amino acids with diverse biological functions. This area includes peptide identification and characterization, database construction, de novo sequencing, functional annotation, omics data integration and systems biology. Artificial intelligence techniques, such as machine learning and natural language processing, aid in the interpretation of peptide sequence data and the generation of biological insights. By using bioinformatics approaches, peptidomics researchers can accelerate peptide discovery, understand their functions and gain insights into complex molecular interactions.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

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

In this editorial context, we aim to leverage the potential of proteogenomics, which integrates genomic and proteomic data, to discover novel biomarkers that can aid in the diagnosis and management of prostate cancer. We highlight the importance of proteogenomics for understanding the functional consequences of somatic mutations in cancer and demonstrating how proteogenomic analysis can provide insights into the effects of genetic alterations on the proteomic landscape and identify potential therapeutic targets. This article also emphasizes the potential of urine analysis for the detection of prostate cancer. Overall, our editorial paper provides general insights on the application of proteogenomics to urine analysis for the identification of novel biomarkers of prostate cancer.

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.

HSPG2 Mutation Association with Immune Checkpoint Inhibitor Outcome in Melanoma and Non-Small Cell Lung Cancer

Immune checkpoint inhibitors (ICIs) markedly promote the survival outcome of advanced melanoma and non-small cell lung cancer (NSCLC). Clinically, favorable ICI treatment efficacy is noticed only in a smaller proportion of patients. Heparan sulfate proteoglycan 2 (HSPG2) frequently mutates in both tumors. Herein, we aim to investigate the immunotherapeutic and immunological roles of HSPG2 mutations in melanoma and NSCLC. A total of 631 melanoma samples and 109 NSCLC samples with both somatic mutational profiles and clinical immunotherapy data were curated. In addition, by using The Cancer Genome Atlas data, genomic and immunological traits behind HSPG2 mutations were elucidated. Melanoma patients with HSPG2 mutations had a markedly extended ICI outcome than other patients. An association between HSPG2 mutations and the improved outcome was further confirmed in NSCLC. In addition, an elevated ICI response rate was presented in HSPG2-mutated NSCLC patients (81.8% vs. 29.7%, p = 0.002). Subsequent analyses revealed that HSPG2-mutated patients had a favorable abundance of response immunocytes, an inferior abundance of suppression immunocytes, enhanced mutational burden, and interferon response-relevant signaling pathways. We uncovered that HSPG2 mutations were predictive of a better ICI response and associated with preferable immunogenicity, which may be considered as a genomic determinant to customize biotherapy strategies.

Tracking Prostate Carcinogenesis over Time through Urine Proteome Profiling in an Animal Model: An Exploratory Approach

Prostate cancer (PCa) is one of the most lethal diseases in men, which justifies the search for new diagnostic tools. The aim of the present study was to gain new insights into the progression of prostate carcinogenesis by analyzing the urine proteome. To this end, urine from healthy animals and animals with prostate adenocarcinoma was analyzed at two time points: 27 and 54 weeks. After 54 weeks, the incidence of pre-neoplastic and neoplastic lesions in the PCa animals was 100%. GeLC-MS/MS and subsequent bioinformatics analyses revealed several proteins involved in prostate carcinogenesis. Increased levels of retinol-binding protein 4 and decreased levels of cadherin-2 appear to be characteristic of early stages of the disease, whereas increased levels of enolase-1 and T-kininogen 2 and decreased levels of isocitrate dehydrogenase 2 describe more advanced stages. With increasing age, urinary levels of clusterin and corticosteroid-binding globulin increased and neprilysin levels decreased, all of which appear to play a role in prostate hyperplasia or carcinogenesis. The present exploratory analysis can be considered as a starting point for studies targeting specific human urine proteins for early detection of age-related maladaptive changes in the prostate that may lead to cancer.