A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans.

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Long-term effects of the chronic administration of doxorubicin on aged skeletal muscle: An exploratory study in mice.

The widely used chemotherapeutic drug doxorubicin (DOX) has been associated with adverse effects on the skeletal muscle, which can persist for years after the end of the treatment. These adverse effects may be exacerbated in older patients, whose skeletal muscle might already be impaired by aging. Nonetheless, the mediators responsible for DOX-induced myotoxicity are still largely unidentified, particularly the ones involved in the long-term effects that negatively affect the quality of life of the patients. Therefore, this study aimed to investigate the long-term effects of the chronic administration of DOX on the soleus muscle of aged mice. For that and to mimic the clinical regimen, a dose of 1.5 mg kg-1 of DOX was administered two times per week for three consecutive weeks in a cumulative dose of 9 mg kg-1 to 19-month-old male mice, which were sacrificed two months after the last administration. Body wasting and the atrophy of the soleus muscle, as measured by a decrease in the cross-sectional area of the soleus muscle fibers, were identified as long-term effects of DOX administration. The atrophy observed was correlated with increased reactive oxygen species production and caspase-3 activity. An impaired skeletal muscle regeneration was also suggested due to the correlation between satellite cells activation and the soleus muscle fibers atrophy. Systemic inflammation, skeletal muscle energy metabolism and neuromuscular junction-related markers do not appear to be involved in the long-term DOX-induced skeletal muscle atrophy. The data provided by this study shed light on the mediators involved in the overlooked long-term DOX-induced myotoxicity, paving the way to the improvement of the quality of life and survival rates of older cancer patients.

Prioritization of genes for translation: a computational approach.

INTRODUCTION: Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation. AREAS COVERED: In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes. EXPERT OPINION: Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

Shaping the future of oral cancer diagnosis: advances in salivary proteomics.

INTRODUCTION: Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for the identification of oral cancer biomarkers. This is particularly important because oral cancer is often diagnosed at late stages with a poor prognosis. AREAS COVERED: The review addresses the evolution of the experimental approaches used in salivary proteomics studies of oral cancer over the years and outlines advantages and pitfalls related to each one. In addition, examines the current landscape of oral cancer biomarker discovery and translation focusing on salivary proteomic studies. This discussion is based on an extensive literature search (PubMed, Scopus and Google Scholar). EXPERT OPINION: The introduction of mass spectrometry has revolutionized the study of salivary proteomics. In the future, the focus will be on refining existing methods and introducing powerful experimental techniques such as mass spectrometry with selected reaction monitoring, which, despite their effectiveness, are still underutilized due to their high cost. In addition, conducting studies with larger cohorts and establishing standardized protocols for salivary proteomics are key challenges that need to be addressed in the coming years.

Exploring omics signature in the cardiovascular response to semaglutide: Mechanistic insights and clinical implications.

BACKGROUND: Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits. RESULTS: This review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti-inflammatory activities and lipid metabolism. These "omics" approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility. CONCLUSION: Future integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.

Restoring Skeletal Muscle Health through Exercise in Breast Cancer Patients and after Receiving Chemotherapy.

Breast cancer (BC) stands out as the most commonly type of cancer diagnosed in women worldwide, and chemotherapy, a key component of treatment, exacerbates cancer-induced skeletal muscle wasting, contributing to adverse health outcomes. Notably, the impact of chemotherapy on skeletal muscle seems to surpass that of the cancer itself, with inflammation identified as a common trigger for muscle wasting in both contexts. In skeletal muscle, pro-inflammatory cytokines modulate pathways crucial for the delicate balance between protein synthesis and breakdown, as well as satellite cell activation and myonuclear accretion. Physical exercise consistently emerges as a crucial therapeutic strategy to counteract cancer and chemotherapy-induced muscle wasting, ultimately enhancing patients' quality of life. However, a "one size fits all" approach does not apply to the prescription of exercise for BC patients, with factors such as age, menopause and comorbidities influencing the response to exercise. Hence, tailored exercise regimens, considering factors such as duration, frequency, intensity, and type, are essential to maximize efficacy in mitigating muscle wasting and improving disease outcomes. Despite the well-established anti-inflammatory role of aerobic exercise, resistance exercise proves equally or more beneficial in terms of mass and strength gain, as well as enhancing quality of life. This review comprehensively explores the molecular pathways affected by distinct exercise regimens in the skeletal muscle of cancer patients during chemotherapy, providing critical insights for precise exercise implementation to prevent skeletal muscle wasting.

Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review.

Bladder cancer (BCa) research relying on Omics approaches has increased over the last few decades, improving the understanding of BCa pathology and contributing to a better molecular classification of BCa subtypes. To gain further insight into the molecular profile underlying the development of BCa, a systematic literature search was performed in PubMed until November 2023, following the PRISMA guidelines. This search enabled the identification of 25 experimental studies using mass spectrometry or nuclear magnetic resonance-based approaches to characterize the metabolite signature associated with BCa. A total of 1562 metabolites were identified to be altered by BCa in different types of samples. Urine samples displayed a higher likelihood of containing metabolites that are also present in bladder tumor tissue and cell line cultures. The data from these comparisons suggest that increased concentrations of L-isoleucine, L-carnitine, oleamide, palmitamide, arachidonic acid and glycoursodeoxycholic acid and decreased content of deoxycytidine, 5-aminolevulinic acid and pantothenic acid should be considered components of a BCa metabolome signature. Overall, molecular profiling of biological samples by metabolomics is a promising approach to identifying potential biomarkers for early diagnosis of different BCa subtypes. However, future studies are needed to understand its biological significance in the context of BCa and to validate its clinical application.

Bioinformatic analysis of the SPs and NFTs proteomes unravel putative biomarker candidates for Alzheimer's disease.

Aging is the main risk factor for the appearance of age-related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks in AD brains. The core of these deposits are predominantly amyloid fibrils in SPs and hyperphosphorylated Tau protein in NFTs, but other molecular components can be found associated with these pathological lesions. Herein, an extensive literature review was carried out to obtain the SPs and NFTs proteomes, followed by a bioinformatic analysis and further putative biomarker validation. For SPs, 857 proteins were recovered, and, for NFTs, 627 proteins of which 375 occur in both groups and represent the common proteome. Gene Ontology (GO) enrichment analysis permitted the identification of biological processes and the molecular functions most associated with these lesions. Analysis of the SPs and NFTs common proteins unraveled pathways and molecular targets linking both histopathological events. Further, validation of a putative phosphotarget arising from the in silico analysis was performed in serum-derived extracellular vesicles from AD patients. This bioinformatic approach contributed to the identification of putative molecular targets, valuable for AD diagnostic or therapeutic intervention.

Exercise training decreases the load and changes the content of circulating SDS-resistant protein aggregates in patients with heart failure with reduced ejection fraction.

BACKGROUND: Heart failure (HF) often disrupts the protein quality control (PQC) system leading to protein aggregate accumulation. Evidence from tissue biopsies showed that exercise restores PQC system in HF; however, little is known about its effects on plasma proteostasis. AIM: To determine the effects of exercise training on the load and composition of plasma SDS-resistant protein aggregates (SRA) in patients with HF with reduced ejection fraction (HFrEF). METHODS: Eighteen patients with HFrEF (age: 63.4 ± 6.5 years; LVEF: 33.4 ± 11.6%) participated in a 12-week combined (aerobic plus resistance) exercise program (60 min/session, twice per week). The load and content of circulating SRA were assessed using D2D SDS-PAGE and mass spectrometry. Cardiorespiratory fitness, quality of life, and circulating levels of high-sensitive C-reactive protein, N-terminal pro-B-type natriuretic peptide (NT-proBNP), haptoglobin and ficolin-3, were also evaluated at baseline and after the exercise program. RESULTS: The exercise program decreased the plasma SRA load (% SRA/total protein: 38.0 ± 8.9 to 36.1 ± 9.7%, p = 0.018; % SRA/soluble fraction: 64.3 ± 27.1 to 59.8 ± 27.7%, p = 0.003). Plasma SRA of HFrEF patients comprised 31 proteins, with α-2-macroglobulin and haptoglobin as the most abundant ones. The exercise training significantly increased haptoglobin plasma levels (1.03 ± 0.40 to 1.11 ± 0.46, p = 0.031), while decreasing its abundance in SRA (1.83 ± 0.54 × 1011 to 1.51 ± 0.59 × 1011, p = 0.049). Cardiorespiratory fitness [16.4(5.9) to 19.0(5.2) ml/kg/min, p = 0.002], quality of life, and circulating NT-proBNP [720.0(850.0) to 587.0(847.3) pg/mL, p = 0.048] levels, also improved after the exercise program. CONCLUSION: Exercise training reduced the plasma SRA load and enhanced PQC, potentially via haptoglobin-mediated action, while improving cardiorespiratory fitness and quality of life of patients with HFrEF.

Galectin-3 in prostate cancer and heart diseases: a biomarker for these two frightening pathologies?

Galectin-3 (Gal-3) belongs to galectin protein family, a type of ß-galactose-binding lectin having more than one evolutionarily conserved domain of carbohydrate recognition. Gal-3 is mainly located in the cytoplasm, but it also enters the nucleus and is secreted into the extracellular environment and biological fluids such as urine, saliva, and serum. It plays an important role in many biological functions, such as angiogenesis, apoptosis, cell differentiation, cell growth, fibrosis, inflammation, host defense, cellular modification, splicing of pre-mRNA, and transformation. Many previous studies have shown that Gal-3 can be used as a diagnostic or prognostic biomarker for heart ailments, kidney diseases, and other major illnesses including cancer. Moreover, it may also play a major role in risk stratification in different diseases, and in this review, we have summarized the potential roles and application of Gal-3 as diagnostic, prognostic, and risk stratifying biomarker from previously reported studies in heart diseases and cancer, with special emphasis on prostate cancer.

Special Issue: "Bioinformatics and Omics Tools".

With the rapid introduction of high-throughput omics approaches such as genomics, transcriptomics, proteomics and metabolomics, the generation of large amounts of data has become a fundamental aspect of modern biological research [...].

Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification.

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.

Long-Term Exposure to Supraphysiological Levels of Testosterone Impacts Rat Submandibular Gland Proteome.

The salivary glands play a central role in the secretion of saliva, whose composition and volume affect oral and overall health. A lesser-explored dimension encompasses the possible changes in salivary gland proteomes in response to fluctuations in sex hormone levels. This study aimed to examine the effects of chronic exposure to testosterone on salivary gland remodeling, particularly focusing on proteomic adaptations. Therefore, male Wistar rats were implanted with subcutaneous testosterone-releasing devices at 14 weeks of age. Their submandibular glands were histologically and molecularly analyzed 47 weeks later. The results underscored a significant increase in gland mass after testosterone exposure, further supported by histologic evidence of granular duct enlargement. Despite increased circulating sex hormones, there was no detectable shift in the tissue levels of estrogen alpha and androgen receptors. GeLC-MS/MS and subsequent bioinformatics identified 308 proteins in the submandibular glands, 12 of which were modulated by testosterone. Of note was the pronounced upregulation of Klk3 and the downregulation of Klk6 and Klk7 after testosterone exposure. Protein-protein interaction analysis with the androgen receptor suggests that Klk3 is a potential target of androgenic signaling, paralleling previous findings in the prostate. This exploratory analysis sheds light on the response of salivary glands to testosterone exposure, providing proteome-level insights into the associated weight and histological changes.

Integration of Automatic Text Mining and Genomic and Proteomic Analysis to Unravel Prostate Cancer Biomarkers.

Prostate cancer (PCa) is the most prevalent noncutaneous cancer among men. The limited accuracy and/or invasive nature of the current diagnostic tools have driven the demand for new and noninvasive biomarkers. Urine as a noninvasive sample that contains prostatic secretions is a promising source of PCa markers. The automatic text-mining functionality of VOSviewer was used to retrieve and create co-occurrence networks of terms associated with PCa. These results were complemented with DisGENET data, a repository of PCa associations, and with a recent bioinformatic analysis integrating all differentially expressed proteins identified in tumor tissue and urine from PCa patients to address the limited term selection of VOSviewer. Afterward, the results were integrated with gene expression data from the Gene Expression Omnibus database to correlate gene and protein levels. This study suggests AXIN2, GSTM2, KLK3, LGALS3, MSMB, PRTFDC1, and SH3RF1 as important entities in PCa context. KLK, LGALS3, and MSMB proteins are common to a previous bioinformatic analysis, and a concordance was found between the levels of gene and protein expression. The applicability of the pipeline presented here was validated by showing altered urinary levels of galectin-3 protein in PCa patients compared to noncancer subjects.

Deciphering specific miRNAs in brain tumors: a 5-miRNA signature in glioblastoma.

MicroRNAs are endogenous non-coding RNAs with a marked impact on the development and progression of brain tumors. However, they commonly share different expression patterns in other types of tumors, thereby exhibiting lack of tissue specificity. Here, an integrative holistic analysis of microarray data is established for deciphering dysregulated miRNAs in glioblastoma, distinguishing them from eight other CNS tumors. The identification of dysregulated miRNAs was performed in a pool of 176 patients, 118 of which diagnosed with glioblastoma. Dysregulated miRNAs commonly expressed in glioblastoma were then discriminated from those co-expressed in other CNS tumors and further characterized. Overall, 21 miRNAs were found to be commonly dysregulated in glioblastoma. Notwithstanding, 16 miRNAs also exhibited a differential expression in at least one other CNS tumor. The remaining 5, specifically, hsa-miR-21-3p, hsa-miR-338-5p, hsa-miR-485-5p, hsa-miR-491-5p and hsa-miR-1290, were solely associated to glioblastoma. This signature is in-depth characterized, with the spotlight on tumor progression, invasion and patient survival. These five endogenous molecules, differentially expressed in glioblastoma, are thus suggested as potential therapeutic targets, modulating several genes involved in major signalling pathways, including MAPK/ERK, calcium, PI3K/AKT, mTOR and Wnt. In summary, these findings lay a foundation for further research on the expression and function of specific patterns of miRNAs expression in glioblastoma, providing reference for potential novel targets.

Cancer- and cardiac-induced cachexia: same fate through different inflammatory mediators?

BACKGROUND: Inflammation is widely recognized as the driving force of cachexia induced by chronic diseases; however, therapies targeting inflammation do not always reverse cachexia. Thus, whether inflammation per se plays an important role in the clinical course of cachectic patients is still a matter of debate. AIMS: To give new insights into cachexia's pathogenesis and diagnosis, we performed a comprehensive literature search on the contribution of inflammatory markers to this syndrome, focusing on the noncommunicable diseases cancer and cardiovascular diseases. METHODS: A systematic review was performed in PubMed using the keywords ("cancer" OR "cardiac" cachexia AND "human" OR "patient" AND "plasma" or "serum"). A total of 744 studies were retrieved and, from these, 206 were selected for full-text screening. In the end, 98 papers focusing on circulating biomarkers of cachexia were identified, which resulted in a list of 113 different mediators. RESULTS: Data collected from the literature highlight the contribution of interleukin-6 (IL-6) and C-reactive protein (CRP) to cachexia, independently of the underlying condition. Despite not being specific, once the diagnosis of cachexia is established, CRP might help to monitor the effectiveness of anti-cachexia therapies. In cardiac diseases, B-type natriuretic peptide (BNP), renin, and obestatin might be putative markers of body wasting, whereas in cancer, growth differentiation factor (GDF) 15, transforming growth factor (TGF)-ß1 and vascular endothelial growth factor (VEGF) C seem to be better markers of this syndrome. Independently of the circulating mediators, NF-κB and JAK/STAT signaling pathways play a key role in bridging inflammation with muscle wasting; however, therapies targeting these pathways were not proven effective for all cachectic patients. CONCLUSION: The critical and integrative analysis performed herein will certainly feed future research focused on the better comprehension of cachexia pathogenesis toward the improvement of its diagnosis and the development of personalized therapies targeting specific cachexia phenotypes.

What can urinary exosomes tell us?

Exosomes are involved in a wide variety of biochemical processes in human body homeostasis. Exosomes also provide important information regarding communications among several organ systems. Additionally, they can serve as molecular vehicles to deliver drugs. Therefore, exosomes have received wide attention in current biomedical research for unraveling pathogenic mechanisms of diseases, searching for novel biomarkers, and discovering new drugs. This paper reviews and discusses the significance of urinary exosomes for a better understanding of human disease pathophysiology and their potential use as therapeutic targets. Isolation methods of exosomes and the latest technological advances are also discussed. Furthermore, novel urinary exosomal biomarkers are highlighted with special emphasis on their clinical applicability (particularly sensitivity, specificity, reliability, and other aspects). Finally, future trends for this field are analyzed and our perspectives are provided.

The role of micropeptides in biology.

Micropeptides are small polypeptides coded by small open-reading frames. Progress in computational biology and the analyses of large-scale transcriptomes and proteomes have revealed that mammalian genomes produce a large number of transcripts encoding micropeptides. Many of these have been previously annotated as long noncoding RNAs. The role of micropeptides in cellular homeostasis maintenance has been demonstrated. This review discusses different types of micropeptides as well as methods to identify them, such as computational approaches, ribosome profiling, and mass spectrometry.

Coronary Artery Disease and Aortic Valve Stenosis: A Urine Proteomics Study.

Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AVS) are heart diseases accounting for most cardiac surgeries. These share many risk factors, such as age, diabetes, hypertension, or obesity, and similar pathogenesis, including endothelial disruption, lipid and immune cell infiltration, inflammation, fibrosis, and calcification. Unsuspected CAD and AVS are sometimes detected opportunistically through echocardiography, coronary angiography, and magnetic resonance. Routine biomarkers for early detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis. With a noninvasive collection, urine is appealing for biomarker assessment. We conducted a shotgun proteomics exploratory analysis of urine from 12 CAD and/or AVS patients and 11 controls to identify putative candidates to differentiate these diseases from healthy subjects. Among the top 20 most dysregulated proteins, TIMP1, MMP2 and vWF stood out, being at least 2.5× increased in patients with CAD/AVS and holding a central position in a network of protein-protein interactions. Moreover, their assessment in an independent cohort (19 CAD/AVS and 10 controls) evidenced strong correlations between urinary TIMP1 and vWF levels and a common cardiovascular risk factor - HDL (r = 0.59, p < 0.05, and r = 0.64, p < 0.01, respectively).

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.