Imperial College London
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Professor Maria Kyrgiou

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Chair in Gynaecologic Oncology
 
 
 
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Contact

 

+44 (0)20 7594 2177m.kyrgiou Website

 
 
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Location

 

Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Giannos:2021:10.3389/fonc.2021.779042,
author = {Giannos, P and Kechagias, K and Bowden, S and Tabassum, N and Paraskevaidi, M and Kyrgiou, M},
doi = {10.3389/fonc.2021.779042},
journal = {Frontiers in Oncology},
pages = {1--8},
title = {PCNA in cervical intraepithelial neoplasia and cervical cancer: an interaction network analysis of differentially expressed genes},
url = {http://dx.doi.org/10.3389/fonc.2021.779042},
volume = {11},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for thedevelopment of markers to optimise cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigatedpatients with cervical disease to identify gene markers whose dysregulated expression and protein interaction interface werelinked with CIN and cervical cancer (CC). Literature search of microarray datasets containing cervical epithelial samples wasconducted in Gene Expression Omnibus and Pubmed/Medline from inception untill March 2021. Retrieved DEGs were used toconstruct two protein-protein interaction (PPI) networks. Module DEGs that overlapped between CIN and CC samples, were rankedbased on 11 topological algorithms. The highest-ranked hub gene was retrieved and its correlation with prognosis, tissueexpression and tumour purity in patients with CC, was evaluated. Screening of the literature yielded 12 microarray datasets(GSE7803, GSE27678, GSE63514, GSE6791, GSE7803, GSE9750, GSE27678, GSE29570, GSE39001, GSE63514, GSE63678, GSE67522). TwoPPI networks from CIN and CC samples were constructed and consisted of 1704 and 3748 DEGs along 21393 and 79828 interactions,respectively. Two gene clusters were retreived in the CIN network and three in the CC network. Multi-algorithmic topologicalanalysis revealed PCNA as the highest ranked hub gene between the two networks, both in terms of expression and interactions.Further analysis revealed that while PCNA was overexpressed in CC tissues, it was correlated with favourable prognosis (log-rank P=0.022, HR=0.58) and tumour purity (P=9.86 × 10-4, partial rho=0.197) in CC patients. This study identified that cervical PCNAexhibited multi-algorithmic topological significance among DEGs from CIN and CC samples. Overall, PCNA may serve as a potentialgene marker of CIN progression. Experimental validation is necessary to examine its value in patients with cervical disease.
AU  - Giannos,P
AU  - Kechagias,K
AU  - Bowden,S
AU  - Tabassum,N
AU  - Paraskevaidi,M
AU  - Kyrgiou,M
DO  - 10.3389/fonc.2021.779042
EP  - 8
PY  - 2021///
SN  - 2234-943X
SP  - 1
TI  - PCNA in cervical intraepithelial neoplasia and cervical cancer: an interaction network analysis of differentially expressed genes
T2  - Frontiers in Oncology
UR  - http://dx.doi.org/10.3389/fonc.2021.779042
UR  - https://www.frontiersin.org/articles/10.3389/fonc.2021.779042/full
UR  - http://hdl.handle.net/10044/1/92790
VL  - 11
ER  -
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