ArticleBMC cancer2015
Novel non-invasive biomarkers that distinguish between benign prostate hyperplasia and prostate cancer.
Article in BMC cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 54 citations in OpenAlex.
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- Assessment of miRNA 106a-5p and 375-3p Expression in the Context of the Wnt/β-Catenin Pathway-Comparison of Prostate Adenocarcinoma and Benign Prostatic Hyperplasia Tissues.International journal of molecular sciences · 2025Article
- Identification of vitronectin as a potential non-invasive biomarker of metastatic breast cancer using a label-free LC-MS/MS approach.Breast cancer research : BCR · 2025Article
- Deciphering Cancer Complexity: Integrative Proteogenomics and Proteomics Approaches for Biomarker Discovery.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications.International journal of molecular sciences · 2024Review
- Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables.Clinical proteomics · 2023Article
- DNA methylation biomarkers distinguishing early-stage prostate cancer from benign prostatic hyperplasia.Prostate international · 2023Article
- Mucins as contrast agent targets for fluorescence-guided surgery of pancreatic cancer.Cancer letters · 2023Review
- The Latest Developments in Using Proteomic Biomarkers from Urine and Serum for Non-Invasive Disease Diagnosis and Prognosis.Biomarker insights · 2023Review
- On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances.International journal of molecular sciences · 2021Review
- Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry.Nature reviews. Urology · 2021Review
- Cdc42-Dependent Transfer of mir301 from Breast Cancer-Derived Extracellular Vesicles Regulates the Matrix Modulating Ability of Astrocytes at the Blood-Brain Barrier.International journal of molecular sciences · 2020Article
- Biomarkers That Differentiate Benign Prostatic Hyperplasia from Prostate Cancer: A Literature Review.Cancer management and research · 2020Review
- Approaches to urinary detection of prostate cancer.Prostate cancer and prostatic diseases · 2019Review
- Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management.Nature reviews. Urology · 2019Review
- Article
- Promise and Implementation of Proteomic Prostate Cancer Biomarkers.Diagnostics (Basel, Switzerland) · 2018Review
- Review
- Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer.Frontiers in oncology · 2017Review
- Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides.Glycoconjugate journal · 2016Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe objective of this study was to discover and to validate novel noninvasive biomarkers that distinguish between benign prostate hyperplasia (BPH) and localized prostate cancer (PCa), thereby helping to solve the diagnostic dilemma confronting clinicians who treat these patients.
methodsQuantitative iTRAQ LC/LC/MS/MS analysis was used to identify proteins that are differentially expressed in the urine of men with BPH compared with those who have localized PCa. These proteins were validated in 173 urine samples from patients diagnosed with BPH (N = 83) and PCa (N = 90). Multivariate logistic regression analysis was used to identify the predictive biomarkers.
resultsThree proteins, β2M, PGA3, and MUC3 were identified by iTRAQ and validated by immunoblot analyses. Univariate analysis demonstrated significant elevations in urinary β2M (P < 0.001), PGA3 (P = 0.006), and MUC3 (P = 0.018) levels found in the urine of PCa patients. Multivariate logistic regression analysis revealed AUC values ranging from 0.618 for MUC3 (P = 0.009), 0.625 for PGA3 (P < 0.008), and 0.668 for β2M (P < 0.001). The combination of all three demonstrated an AUC of 0.710 (95% CI: 0.631 - 0.788, P < 0.001); diagnostic accuracy improved even more when these data were combined with PSA categories (AUC = 0.812, (95% CI: 0.740 - 0.885, P < 0.001).
conclusionsUrinary β2M, PGA3, and MUC3, when analyzed alone or when multiplexed with clinically defined categories of PSA, may be clinically useful in noninvasively resolving the dilemma of effectively discriminating between BPH and localized PCa.
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