Six potential biomarkers for bladder cancer: key proteins in cell-cycle division and apoptosis pathways.

Autor: Inal Gültekin G; Department of Physiology, Faculty of Medicine, Istanbul Okan University, Tepeören Campus, Tuzla, Istanbul, Turkey. guldal.inal@okan.edu.tr.; Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey. guldal.inal@okan.edu.tr., Timirci Kahraman Ö; Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey., Işbilen M; Department of Biostatistics and Bioinformatics, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey., Durmuş S; Department of Bioengineering, Faculty of Engineering, Gebze Technical University, Kocaeli, Turkey., Çakir T; Department of Bioengineering, Faculty of Engineering, Gebze Technical University, Kocaeli, Turkey., Yaylim İ; Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey., Isbir T; Department of Molecular Medicine, Faculty of Medicine, Yeditepe University, Kayışdağı, Istanbul, Turkey.
Jazyk: angličtina
Zdroj: Journal of the Egyptian National Cancer Institute [J Egypt Natl Canc Inst] 2022 Dec 19; Vol. 34 (1), pp. 54. Date of Electronic Publication: 2022 Dec 19.
DOI: 10.1186/s43046-022-00153-0
Abstrakt: Background: The bladder cancer (BC) pathology is caused by both exogenous environmental and endogenous molecular factors. Several genes have been implicated, but the molecular pathogenesis of BC and its subtypes remains debatable. The bioinformatic analysis evaluates high numbers of proteins in a single study, increasing the opportunity to identify possible biomarkers for disorders.
Methods: The aim of this study is to identify biomarkers for the identification of BC using several bioinformatic analytical tools and methods. BC and normal samples were compared for each probeset with T test in GSE13507 and GSE37817 datasets, and statistical probesets were verified with GSE52519 and E-MTAB-1940 datasets. Differential gene expression, hierarchical clustering, gene ontology enrichment analysis, and heuristic online phenotype prediction algorithm methods were utilized. Statistically significant proteins were assessed in the Human Protein Atlas database. GSE13507 (6271 probesets) and GSE37817 (3267 probesets) data were significant after the extraction of probesets without gene annotation information. Common probesets in both datasets (2888) were further narrowed by analyzing the first 100 upregulated and downregulated probesets in BC samples.
Results: Among the total 400 probesets, 68 were significant for both datasets with similar fold-change values (Pearson r: 0.995). Protein-protein interaction networks demonstrated strong interactions between CCNB1, BUB1B, and AURKB. The HPA database revealed similar protein expression levels for CKAP2L, AURKB, APIP, and LGALS3 both for BC and control samples.
Conclusion: This study disclosed six candidate biomarkers for the early diagnosis of BC. It is suggested that these candidate proteins be investigated in a wet lab to identify their functions in BC pathology and possible treatment approaches.
(© 2022. The Author(s).)
Databáze: MEDLINE
Externí odkaz: