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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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