eISSN: 1896-9151
ISSN: 1734-1922
Archives of Medical Science
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SCImago Journal & Country Rank
3/2019
vol. 15
 
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Oncological Gynecology
abstract:
Basic research

Co-expression network analysis of the lncRNAs and mRNAs associated with cervical cancer progression

Li Jiang, Li Hong, Wenwu Yang, Yuzi Zhao, Aili Tan, Yang Li

Arch Med Sci 2019; 15 (3): 754–764
Online publish date: 2019/04/30
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Introduction
Cervical cancer is the second most common type of cancer and the third leading cause of cancer deaths in females in developing countries. Recent studies showed that long non-coding RNAs play a key role in human cancers. However, the molecular mechanisms underlying the initiation and progression of cervical cancer remained to be further explored.

Material and methods
In this study, we explored the differential expression of lncRNAs and mRNAs in cervical cancer progression by analyzing the public dataset GSE63514. Next, PPI and co-expression networks were constructed to reveal the potential roles of cervical cancer related mRNAs and lncRNAs. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to explore functions of differentially expressed genes (DEGs) in cervical cancer.

Results
In the present study, we observed that 3021 mRNAs were up-regulated and 1605 mRNAs were down-regulated in cervical cancer progression. Meanwhile, we for the first time found that 172 lncRNAs were up-regulated and 106 lncRNAs were down-regulated in cervical cancer progression. Co-expression network analysis showed that lncRNAs were widely co-expressed with cell cycle related genes in cervical cancer, implicating the important roles of these lncRNAs in cell proliferation regulation. Of note, we identified two hub lncRNA-mRNA networks involved in regulating various biological processes in cervical cancer progression.

Conclusions
Our results identified key mRNAs and lncRNAs in cervical cancer progression. This study will provide novel insights to explore the potential mechanisms underlying cervical cancer progression.

keywords:

long non-coding RNAs, cervical cancer, protein-protein interaction analysis, expression profiling

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