Profiling Analysis Reveals the Crucial Role of the Endogenous Peptides in Bladder Cancer Progression

Onco Targets Ther. 2020 Dec 3:13:12443-12455. doi: 10.2147/OTT.S281713. eCollection 2020.

Abstract

Background: Peptide drugs provide promising regimes in bladder cancer. In order to identify potential bioactive peptides involved in bladder cancer, we performed the present study.

Methods: Liquid chromatography/mass spectrometry assay was used to compare the endogenous peptides between bladder cancer and normal control. The potential biological functions of these dysregulated peptides are assessed by GO analysis and KEGG pathway analysis of their precursors. The SMART and UniProt databases are used to identify the sequences of the dysregulated peptides located in the functional domains. The Open Targets Platform database was used to investigate the precursors related to metabolic diseases.

Results: A total of 9 up-regulated peptides and 110 down-regulated peptides in bladder cancer compared with normal control were identified (fold change > 1.2, P < 0.05). The MW of these dysregulated peptides ranged from 500 Da to 2500 Da and the MW of all identified peptides was below 3500 Da. The GO and KEGG pathway analysis indicated that these dysregulated peptides could play an important role in bladder cancer. Our further analysis revealed that 45HFNPRFNAHGDAN 57 derived from LGALS1 and those peptides derived from P4HB and SERPINA1 might be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Conclusion: In the present study, we have identified the profile of the peptides significantly dysregulated in bladder cancer. Moreover, using bioinformatic analysis, we found the peptides derived from LGALS1, P4HB and SERPINA1 could be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Keywords: bladder cancer; peptide; progression; therapeutic target.

Grants and funding

This work was financially supported by the National Natural Science Foundation of China (81772712, 81702569), the Natural Science Foundation of Jiangsu Province (BK20170151).