<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ahn JH</submitter><funding>Ah-Ram Kim</funding><pagination>395</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8950253</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12(3)</volume><pubmed_abstract>Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.</pubmed_abstract><journal>Life (Basel, Switzerland)</journal><pubmed_title>Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers.</pubmed_title><pmcid>PMC8950253</pmcid><funding_grant_id>This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (NRF-2019R1I1A2A01063045).</funding_grant_id><pubmed_authors>Ahn JH</pubmed_authors><pubmed_authors>Kim A</pubmed_authors><pubmed_authors>Kim AR</pubmed_authors><pubmed_authors>Kim EM</pubmed_authors><pubmed_authors>Kang CK</pubmed_authors></additional><is_claimable>false</is_claimable><name>Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers.</name><description>Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Mar</publication><modification>2025-04-19T12:10:50.273Z</modification><creation>2025-04-19T12:10:50.273Z</creation></dates><accession>S-EPMC8950253</accession><cross_references><pubmed>35330146</pubmed><doi>10.3390/life12030395</doi></cross_references></HashMap>