Screening urinary differential proteins in bladder urothelial carcinoma based on ITRAQ technique-MRM-R language strategy
- Journal of Third Military Medical University Vol. 43, Issue 10, Pages: 982-988(2021)
- 作者机构：
- 作者简介：
- 基金信息：the Project of Science and Technology Plan of Hebei Province(H2015209164)
DOI：10.16016/j.1000-5404.202011204
CLC：Received：23 November 2020，
Published：30 May 2021
- 稿件说明：
移动端阅览
Linyao WANG, Changying LI, Jianmin LI, et al. Screening urinary differential proteins in bladder urothelial carcinoma based on ITRAQ technique-MRM-R language strategy[J]. Journal of Third Military Medical University, 2021, 43(10): 982-988.
Linyao WANG, Changying LI, Jianmin LI, et al. Screening urinary differential proteins in bladder urothelial carcinoma based on ITRAQ technique-MRM-R language strategy[J]. Journal of Third Military Medical University, 2021, 43(10): 982-988. DOI： 10.16016/j.1000-5404.202011204.
摘要
Abstract
Objective
2
To construct a urinary differential proteins dataset for bladder urothelial carcinoma (BUC) so as to screen the core differentially expressed proteins (DEPs) and then validate them.
Methods
2
Preoperative urine samples were collected from 78 hospitalized BUC patients (55 males
23 females; 68.9±6.6 years old) in the Urology Department of the Second Hospital of Tianjin Medical University from January 2015 to November 2016. At the same time period
urine samples from 51 healthy volunteers were also collected for control group analysis (34 males
17 females; 60.6±11.0 years old). Using isobaric tags for relative and absolute quantitation (iTRAQ) technology
comparative proteomics study was conducted on a total of 6 mixed urine samples
including 4 cases in the BUC group and 2 cases in the control group
to find out the DEPs between the 2 groups. The top 20 DEPs were selected for multiple reaction monitoring (MRM) verification; Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out with R package
clusterProfiler
and Gene Ontology (GO) enrichment analysis was subsequently performed with org.Hs.eg.db package to preliminarily select the meaningful differential proteins for BUC urinary differential protein dataset. Then the Protein-Protein Interaction (PPI) map was plot using R language to screen the core differential proteins. Furthermore
enzyme-linked immunosorbent assay (ELISA) was applied to verify the difference of core differential proteins in the urine samples.
Results
2
A total of 101 BUC urinary DEPs were obtained
of which 37 proteins were up-regulated and 64 down-regulated. MRM detected 10 DEPs. KEGG analysis found that there were 11 DEPs significantly enriched in 2 metabolic pathways
namely other chitosan degradation and complement and blood coagulation cascade. GO analysis displayed that totally 54 DEPs were mainly involved in cell adhesion molecule binding
carboxylic acid binding
organic acid binding
glycosaminoglycan binding
endopeptidase activity and other biological processes. Combining the 3 results
the BUC urinary differential protein dataset was finally established
including 69 proteins in total. By protein interaction analysis
APOE and APOA4 were screened as the core differential proteins. ELISA results showed that the average concentration of APOE was 0.55 pg/mL and 0.30 pg/mL in the BUC group and the control group
respectively
and that of APOA4 was 3.33 ng/mL and 7.01 ng/mL respectively
both with significant increases (
P
<
0.05).
Conclusion
2
The application of iTRAQ-MRM-R language strategy can assist the construction of BUC urinary differential protein dataset
and further screen out the core DEPs
providing a new target for the diagnosis and treatment of BUC.
关键词
Keywords
references
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