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4D label-free quantitative proteomics Analysis and Bioinformatics study of proteins in Retinoblastoma

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Purpose: To analysis proteins in the tissue of Retinoblastoma, and to investigate their potential roles in retinoblastoma. Methods: The retinas of retinoblastoma were collected from 4 retinoblastoma patients(2 females, 2 males; average age was 5.10±3.12 years old) in our hospital from May, 2021 to August, 2016. The retinas of healthy eyes were from 6 eyeball donors(3 females, 3 males; average age was 15.30±2.52 years old).4D label-free quantitative proteomics was used to analyze proteins in the retinoblastoma retinas and healthy eyeball retinas. Proteins with a fold change of >2. 0 or <0.5 were considered to be significantly differentially expressed (with corrected p-values of <0.1). The identified proteins were subjected to subsequent gene ontology analysis using the DAVID database. Then we confirmed the targeted proteins with qRT-PCR. Results: 1453 proteins that expressed differently between the retinoblastoma and healthy eyeball retinas were identified using4D label-free quantitative proteomics analysis. Of these proteins, 739 were down-regulated, and 714 were up-regulated. On the basis of biological processes in gene ontology, the identified proteins were mainly involved in Amino acid biosynthesis, DNA replication, and nucleocytoplasmic transport pathways. Based on PPI analysis, Based on PPI analysis, Minichromosome maintenance family (MCMs) may have potential roles in the pathogenesis of retinoblastoma. Then we confirmed with qRT-PCR that MCMs were up-regulated in retinoblastoma retinas. Conclusion: This study is the first to identify 1453 proteins associated with retinoblastoma with 4D label-free quantitative proteomics technology. Data in our study will aid in providing a better understanding of retinoblastoma.
Title: 4D label-free quantitative proteomics Analysis and Bioinformatics study of proteins in Retinoblastoma
Description:
Purpose: To analysis proteins in the tissue of Retinoblastoma, and to investigate their potential roles in retinoblastoma.
Methods: The retinas of retinoblastoma were collected from 4 retinoblastoma patients(2 females, 2 males; average age was 5.
10±3.
12 years old) in our hospital from May, 2021 to August, 2016.
The retinas of healthy eyes were from 6 eyeball donors(3 females, 3 males; average age was 15.
30±2.
52 years old).
4D label-free quantitative proteomics was used to analyze proteins in the retinoblastoma retinas and healthy eyeball retinas.
Proteins with a fold change of >2.
0 or <0.
5 were considered to be significantly differentially expressed (with corrected p-values of <0.
1).
The identified proteins were subjected to subsequent gene ontology analysis using the DAVID database.
Then we confirmed the targeted proteins with qRT-PCR.
Results: 1453 proteins that expressed differently between the retinoblastoma and healthy eyeball retinas were identified using4D label-free quantitative proteomics analysis.
Of these proteins, 739 were down-regulated, and 714 were up-regulated.
On the basis of biological processes in gene ontology, the identified proteins were mainly involved in Amino acid biosynthesis, DNA replication, and nucleocytoplasmic transport pathways.
Based on PPI analysis, Based on PPI analysis, Minichromosome maintenance family (MCMs) may have potential roles in the pathogenesis of retinoblastoma.
Then we confirmed with qRT-PCR that MCMs were up-regulated in retinoblastoma retinas.
Conclusion: This study is the first to identify 1453 proteins associated with retinoblastoma with 4D label-free quantitative proteomics technology.
Data in our study will aid in providing a better understanding of retinoblastoma.

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