PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes
The investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for the development of markers to optimize cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigated patients with cervical disease to identify gene marker...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:f42760d2244e4bd2b6899718c35628242021-12-01T06:06:40ZPCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes2234-943X10.3389/fonc.2021.779042https://doaj.org/article/f42760d2244e4bd2b6899718c35628242021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.779042/fullhttps://doaj.org/toc/2234-943XThe investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for the development of markers to optimize cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigated patients with cervical disease to identify gene markers whose dysregulated expression and protein interaction interface were linked with CIN and cervical cancer (CC). Literature search of microarray datasets containing cervical epithelial samples was conducted in Gene Expression Omnibus and Pubmed/Medline from inception until March 2021. Retrieved DEGs were used to construct two protein-protein interaction (PPI) networks. Module DEGs that overlapped between CIN and CC samples, were ranked based on 11 topological algorithms. The highest-ranked hub gene was retrieved and its correlation with prognosis, tissue expression and tumor purity in patients with CC, was evaluated. Screening of the literature yielded 9 microarray datasets (GSE7803, GSE27678, GSE63514, GSE6791, GSE9750, GSE29570, GSE39001, GSE63678, GSE67522). Two PPI 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 retrieved in the CIN network and three in the CC network. Multi-algorithmic topological analysis 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 favorable prognosis (log-rank P=0.022, HR=0.58) and tumor purity (P=9.86 × 10-4, partial rho=0.197) in CC patients. This study identified that cervical PCNA exhibited multi-algorithmic topological significance among DEGs from CIN and CC samples. Overall, PCNA may serve as a potential gene marker of CIN progression. Experimental validation is necessary to examine its value in patients with cervical disease.Panagiotis GiannosPanagiotis GiannosKonstantinos S. KechagiasKonstantinos S. KechagiasKonstantinos S. KechagiasSarah BowdenSarah BowdenNeha TabassumMaria ParaskevaidiMaria ParaskevaidiMaria KyrgiouMaria KyrgiouMaria KyrgiouMaria KyrgiouFrontiers Media S.A.articlecervical intraepithelial neoplasiaCINcervical cancergene biomarkerscervical diseaseNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021) |
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| collection |
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| topic |
cervical intraepithelial neoplasia CIN cervical cancer gene biomarkers cervical disease Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 |
| spellingShingle |
cervical intraepithelial neoplasia CIN cervical cancer gene biomarkers cervical disease Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Panagiotis Giannos Panagiotis Giannos Konstantinos S. Kechagias Konstantinos S. Kechagias Konstantinos S. Kechagias Sarah Bowden Sarah Bowden Neha Tabassum Maria Paraskevaidi Maria Paraskevaidi Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| description |
The investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for the development of markers to optimize cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigated patients with cervical disease to identify gene markers whose dysregulated expression and protein interaction interface were linked with CIN and cervical cancer (CC). Literature search of microarray datasets containing cervical epithelial samples was conducted in Gene Expression Omnibus and Pubmed/Medline from inception until March 2021. Retrieved DEGs were used to construct two protein-protein interaction (PPI) networks. Module DEGs that overlapped between CIN and CC samples, were ranked based on 11 topological algorithms. The highest-ranked hub gene was retrieved and its correlation with prognosis, tissue expression and tumor purity in patients with CC, was evaluated. Screening of the literature yielded 9 microarray datasets (GSE7803, GSE27678, GSE63514, GSE6791, GSE9750, GSE29570, GSE39001, GSE63678, GSE67522). Two PPI 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 retrieved in the CIN network and three in the CC network. Multi-algorithmic topological analysis 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 favorable prognosis (log-rank P=0.022, HR=0.58) and tumor purity (P=9.86 × 10-4, partial rho=0.197) in CC patients. This study identified that cervical PCNA exhibited multi-algorithmic topological significance among DEGs from CIN and CC samples. Overall, PCNA may serve as a potential gene marker of CIN progression. Experimental validation is necessary to examine its value in patients with cervical disease. |
| format |
article |
| author |
Panagiotis Giannos Panagiotis Giannos Konstantinos S. Kechagias Konstantinos S. Kechagias Konstantinos S. Kechagias Sarah Bowden Sarah Bowden Neha Tabassum Maria Paraskevaidi Maria Paraskevaidi Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou |
| author_facet |
Panagiotis Giannos Panagiotis Giannos Konstantinos S. Kechagias Konstantinos S. Kechagias Konstantinos S. Kechagias Sarah Bowden Sarah Bowden Neha Tabassum Maria Paraskevaidi Maria Paraskevaidi Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou Maria Kyrgiou |
| author_sort |
Panagiotis Giannos |
| title |
PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| title_short |
PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| title_full |
PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| title_fullStr |
PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| title_full_unstemmed |
PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes |
| title_sort |
pcna in cervical intraepithelial neoplasia and cervical cancer: an interaction network analysis of differentially expressed genes |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/f42760d2244e4bd2b6899718c3562824 |
| work_keys_str_mv |
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| _version_ |
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