Proteomics Profiling of Bladder Cancer Tissues from Early to Advanced Stages Reveals NNMT and GALK1 as Biomarkers for Early Detection and Prognosis of BCa

Author:

Davalieva Katarina1ORCID,Kiprijanovska Sanja1,Ivanovski Ognen2,Trifunovski Aleksandar2,Saidi Skender2,Dimovski Aleksandar13,Popov Zivko456

Affiliation:

1. Research Centre for Genetic Engineering and Biotechnology “Georgi D Efremov”, Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia

2. Clinical Centre “Mother Theresa”, University Clinic for Urology, 1000 Skopje, North Macedonia

3. Faculty of Pharmacy, University “St. Cyril and Methodius”, 1000 Skopje, North Macedonia

4. Clinical Hospital “Acibadem Sistina”, 1000 Skopje, North Macedonia

5. Medical Faculty, University “St. Cyril and Methodius”, 1000 Skopje, North Macedonia

6. Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia

Abstract

The high recurrence rate and invasive diagnostic and monitoring methods in bladder cancer (BCa) clinical management require the development of new non-invasive molecular tools for early detection, particularly for low-grade and low-stage BCa as well as for risk stratification. By using an in-solution digestion method and label-free data-independent LC-MS/MS coupled with ion mobility, we profiled the BCa tissues from initiation to advanced stages and confidently identified and quantified 1619 proteins (≥2 peptides). A statistically significant difference in abundance (Anova ≤ 0.05) showed 494 proteins. Significant correlation with stage with steady up or down with BCa stages showed 15 proteins. Testing of NNMT, GALK1, and HTRA1 in urine samples showed excellent diagnostic potential for NNMT and GALK1 with AUC of 1.000 (95% CI: 1.000–1.000; p < 0.0001) and 0.801 (95% CI: 0.655–0.947; p < 0.0001), respectively. NNMT and GALK1 also showed very good potential in discriminating non-invasive low-grade from invasive high-grade BCa with AUC of 0.763 (95% CI: 0.606–0.921; p = 0.001) and 0.801 (95% CI: 0.653–0.950; p < 0.0001), respectively. The combination of NNMT and GALK1 increased prognostic accuracy (AUC = 0.813). Our results broaden the range of potential novel candidates for non-invasive BCa diagnosis and prognosis.

Funder

ICGEB

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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