A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Frontiers in Medicine

Tara K. Sigdel¹  Minnie M. Sarwal¹  Alvin Y. Liu²  Tujin Shi³  Wei-Jun Qian³  Adam C. Swensen³  Yinyin Ye³  Alexander C. Fang³  Carrie D. Nicora³  Jingtang He³ 

[1] Department of Surgery, University of California, San Francisco, San Francisco, CA, United States;Department of Urology, University of Washington, Seattle, WA, United States;Integrative Omics, Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA, United States;

关键词: LC-MS/MS;    urine proteome;    proteomics;    urinary biomarkers;    prostate cancer;    kidney disease;   

DOI  :  10.3389/fmed.2021.548212

来源: Frontiers

【 摘 要 】

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

【 授权许可】

CC BY