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. 2023 Mar 14;25(4):173.
doi: 10.3892/ol.2023.13759. eCollection 2023 Apr.

Urinary endogenous peptides as biomarkers for prostate cancer

Affiliations

Urinary endogenous peptides as biomarkers for prostate cancer

Cristine De Souza Dutra et al. Oncol Lett. .

Abstract

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.

Keywords: biomarkers; endogenous peptides; mass spectrometry; prostate cancer; urine; uromodulin.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1.
Figure 1.
Urinary peptides with differential abundance between the study groups. Peak area values of UMOD peptides significantly altered between BPH and PCa, and control and PCa groups. Differences between groups were analyzed using unpaired moderated t-test (empirical Bayes Limma approach) with Benjamini-Hochberg correction. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. PCa, prostate cancer; BPH, benign prostatic hyperplasia; UMOD-P, uromodulin peptide.
Figure 2.
Figure 2.
Performance of urinary peptides as biomarkers for PCa detection. ROC analyses were performed using log2-transformed precursor peak area values of UMOD peptides in (A) control vs. PCa, and (B) BPH vs. PCa groups. (C) ROC curve data for the different comparisons between the study groups. ROC, receiver operating characteristic; PCa, prostate cancer; BPH, benign prostatic hyperplasia; UMOD-P, uromodulin peptide; CI, confidence interval; n.a., not applicable.
Figure 3.
Figure 3.
ROC curves for urinary peptide panels and PSA levels. Comparative ROC analysis using peptide combinations or PSA levels for discriminating (A) control vs. PCa, and (B) BPH vs. PCa groups. Data for the respective ROC curves are shown in (C) and (D), respectively. ROC, receiver operating characteristic; PCa, prostate cancer; BPH, benign prostatic hyperplasia; PSA, prostate-specific antigen; UMOD-P, uromodulin peptide; CI, confidence interval.
Figure 4.
Figure 4.
Predicted proteases involved in the generation of UMOD peptides. UMOD urinary peptides originate from a region near to C-terminal of the precursor uromodulin protein. (A) Peptides identified in our study are in bold red and the predicted cleavage sites and proteases are indicated by dashed lines. (B) Additional cleavage sites predicted for UMOD-P3. (C) Expression profile of predicted proteases in PCa and normal tissue. Data were retrieved from TCGA using UALCAN portal and correspond to normal and PCa tissues from different individuals. Statistical analysis was performed using unpaired Welch's t-test. PCa, prostate cancer; SP, signal peptide; EGF, epidermal growth factor; ZP, zona pellucida; GPI, glycosylphosphatidylinositol.

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