Transcriptomic Analysis of the Aquaporin Gene Family and Associated Interactors in Rectal Cancer

(E-pub Ahead of Print)

Author(s): Dimitrios E. Magouliotis, Vasiliki S. Tasiopoulou, Ioannis Baloyiannis, Ioannis Mamaloudis, George Tzovaras*.

Journal Name: MicroRNA

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Background: Rectal cancer (RC) is a common type of cancer with poor prognosis. The identification of biomarkers regarding RC diagnosis, monitoring, and prognosis is crucial.

Objectives: The purpose of the present study was to aevaluate the differential expression of the aquaporin (AQP) gene family network in RC, and the effect of radiotherapy (RT) on their expression profile, so as to indicate novel biomarkers and prognostic factors.

Methods: We used data mining techniques to construct the network of the AQP-associated genes so as to determine the differentially expressed genes (DEGs) in RC and in irradiated as compared to non-irradiated RC patients. Furthermore, survival data of The Cancer Genome Atlas (TCGA) were analysed so as to assess the prognostic role of the DEGs, along with the functional enrichment of gene ontologies and miRNAs related to the DEGs in RC.

Results: Microarray data of one Pubmed GEO dataset was extracted, incorporating 22 RC and 20 normal rectal tissue samples. Eight DEGs were reported. Four DEGs were up-regulated and four downregulated in RC. Correlations were identified among the DEGs. Deming regression analysis was performed in order to demonstrate the equations describing these correlations. One gene (Aquaporin 3) was downregulated in irradiated RC samples compared with non-irradiated. The most significantly affected biological pathways and miRNAs were identified by functional enrichment analysis.

Conclusion: The present study demonstrates an eight-gene molecular panel that could facilitate as biomarkers regarding RC patients, which are potential targets of five miRNA families. Finally, our results highlight the effect of radiotherapy on AQPs and the associated pathways in RC.

Keywords: rectal cancer, aquaporin, biomarker, aqp3, radiotherapy, miRNA, transcriptomics, in silico

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(E-pub Ahead of Print)
DOI: 10.2174/2211536608666190917153332

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