Urinary endogenous peptides as biomarkers for prostate cancer

Prostate cancer (PCa) is one of the most prevalent types of cancer in men worldwide; however, the main diagnostic tests available for PCa have limitations and a biopsy is required for histopathological confirmation of the disease. Prostate-specific antigen (PSA) is the main biomarker used for the early detection of PCa, but an elevated serum concentration is not cancer-specific. Therefore, there is a need for the discovery of new non-invasive biomarkers that can accurately diagnose PCa. The present study used trichloroacetic acid-induced protein precipitation and liquid chromatography-mass spectrometry to profile endogenous peptides in urine samples from patients with PCa (n=33), benign prostatic hyperplasia (n=25) and healthy individuals (n=28). Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of urinary peptides. In addition, Proteasix tool was used for in silico prediction of protease cleavage sites. Five urinary peptides derived from uromodulin were revealed to be significantly altered between the study groups, all of which were less abundant in the PCa group. This peptide panel showed a high potential to discriminate between the study groups, resulting in area under the curve (AUC) values between 0.788 and 0.951. In addition, urinary peptides outperformed PSA in discriminating between malignant and benign prostate conditions (AUC=0.847), showing high sensitivity (81.82%) and specificity (88%). From in silico analyses, the proteases HTRA2, KLK3, KLK4, KLK14 and MMP25 were identified as potentially involved in the degradation of uromodulin peptides in the urine of patients with PCa. In conclusion, the present study allowed the identification of urinary peptides with potential for use as non-invasive biomarkers in PCa diagnosis.

[1]  R. González-Barrios,et al.  The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches , 2022, Prostate Cancer and Prostatic Diseases.

[2]  Tariq Ahmad Masoodi,et al.  Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments , 2022, Molecular Cancer.

[3]  A. Brazma,et al.  The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences , 2021, Nucleic Acids Res..

[4]  H. Mischak,et al.  Reproducibility Evaluation of Urinary Peptide Detection Using CE-MS , 2021, Molecules.

[5]  Pu Zhang,et al.  Advances in Research on Bladder Cancer Targeting Peptides: a Review , 2021, Cell Biochemistry and Biophysics.

[6]  I. Endo,et al.  Urine as a Source of Liquid Biopsy for Cancer , 2021, Cancers.

[7]  A. Jemal,et al.  Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries , 2021, CA: a cancer journal for clinicians.

[8]  P. Nelson,et al.  Genomic and phenotypic heterogeneity in prostate cancer , 2020, Nature Reviews Urology.

[9]  S. Pennington,et al.  Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management , 2020, Clinical proteomics.

[10]  E. Diamandis,et al.  Peptidomic Analysis of Urine from Youths with Early Type 1 Diabetes Reveals Novel Bioactivity of Uromodulin Peptides In Vitro* , 2019, Molecular & Cellular Proteomics.

[11]  Pingli Wei,et al.  Urinary Metabolomic and Proteomic Analyses in a Mouse Model of Prostatic Inflammation. , 2019, Urine.

[12]  Kevin M. Koo,et al.  Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management , 2019, Nature Reviews Urology.

[13]  Fredrik Levander,et al.  NormalyzerDE: Online Tool for Improved Normalization of Omics Expression Data and High-Sensitivity Differential Expression Analysis. , 2018, Journal of proteome research.

[14]  M. Moses,et al.  Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer , 2018, Oncotarget.

[15]  G. Arrigoni,et al.  MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers , 2018, Clinical Proteomics.

[16]  R. Khokha,et al.  Metalloproteinases in extracellular vesicles. , 2017, Biochimica et biophysica acta. Molecular cell research.

[17]  Thomas A. Geddes,et al.  Multiplexed Temporal Quantification of the Exercise-regulated Plasma Peptidome* , 2017, Molecular & Cellular Proteomics.

[18]  H. Moch,et al.  Urinary Biomarkers for Prostate Cancer. , 2017, Current drug metabolism.

[19]  Chad J. Creighton,et al.  UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses , 2017, Neoplasia.

[20]  C. Delles,et al.  Polymerization-Incompetent Uromodulin in the Pregnant Stroke-Prone Spontaneously Hypertensive Rat , 2017, Hypertension.

[21]  K. Nelson,et al.  Comprehensive Metaproteomic Analyses of Urine in the Presence and Absence of Neutrophil-Associated Inflammation in the Urinary Tract , 2017, Theranostics.

[22]  M. Manns,et al.  Urinary Peptide Analysis Differentiates Pancreatic Cancer From Chronic Pancreatitis , 2016, Pancreas.

[23]  J. Persson,et al.  Use of two gene panels for prostate cancer diagnosis and patient risk stratification , 2016, Tumor Biology.

[24]  A. Vlahou,et al.  Identification of ageing-associated naturally occurring peptides in human urine , 2015, Oncotarget.

[25]  J. Clements,et al.  Kallikrein-Related Peptidases in Prostate Cancer: From Molecular Function to Clinical Application , 2014, EJIFCC.

[26]  S. Hong Kallikreins as Biomarkers for Prostate Cancer , 2014, BioMed research international.

[27]  J. Schalken,et al.  Urinary biomarkers for prostate cancer: a review. , 2013, Asian journal of andrology.

[28]  Robert Stevens,et al.  Proteasix: A tool for automated and large‐scale prediction of proteases involved in naturally occurring peptide generation , 2013, Proteomics.

[29]  Peter J. Selby,et al.  Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers , 2013, Nature Reviews Urology.

[30]  T. Kislinger,et al.  Identification of prostate-enriched proteins by in-depth proteomic analyses of expressed prostatic secretions in urine. , 2012, Journal of proteome research.

[31]  Michael J. MacCoss,et al.  Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline , 2012, Molecular & Cellular Proteomics.

[32]  A. Partin,et al.  Review of the literature: PCA3 for prostate cancer risk assessment and prognostication. , 2011, Reviews in urology.

[33]  Thomas Wiegel,et al.  EAU guidelines on prostate cancer. Part 1: screening, diagnosis, and treatment of clinically localised disease. , 2011, European urology.

[34]  M. Girolami,et al.  Naturally Occurring Human Urinary Peptides for Use in Diagnosis of Chronic Kidney Disease* , 2010, Molecular & Cellular Proteomics.

[35]  Robert A. Gardiner,et al.  Markers for Detection of Prostate Cancer , 2010, Cancers.

[36]  A. Imai,et al.  Protein profiling of post-prostatic massage urine specimens by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to discriminate between prostate cancer and benign lesions. , 2009, Oncology reports.

[37]  A. Dominiczak,et al.  Body fluid proteomics for biomarker discovery: lessons from the past hold the key to success in the future. , 2007, Journal of proteome research.

[38]  R. Caprioli,et al.  Detection of pre-neoplastic and neoplastic prostate disease by MALDI profiling of urine. , 2007, Biochemical and biophysical research communications.

[39]  A. Semjonow,et al.  Pilot study of capillary electrophoresis coupled to mass spectrometry as a tool to define potential prostate cancer biomarkers in urine , 2005, Electrophoresis.

[40]  R. Ball,et al.  Identification of degradome components associated with prostate cancer progression by expression analysis of human prostatic tissues , 2005, British Journal of Cancer.

[41]  J. Crowley,et al.  Prevalence of prostate cancer among men with a prostate-specific antigen level < or =4.0 ng per milliliter. , 2004, The New England journal of medicine.

[42]  D. Cavallone,et al.  Tamm-Horsfall glycoprotein: biology and clinical relevance. , 2003, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[43]  A. Partin,et al.  PSA levels and the probability of prostate cancer on biopsy , 2002 .