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Article

Screening of FOXD3 targets in lung cancer via bioinformatics analysis

  • Authors:
    • Wenhua Jiang
    • Pengfei Liu
    • Xiaodong Li
  • View Affiliations / Copyright

    Affiliations: Department of Radiotherapy, The Second Hospital of Tianjin Medical University, Tianjin 300211, P.R. China, Department of Lymphoma, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, P.R. China
  • Pages: 3214-3220
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    Published online on: December 21, 2017
       https://doi.org/10.3892/ol.2017.7685
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Abstract

The purpose of the present study was to explore the targets of forkhead box D3 (FOXD3) in lung cancer, and thus contribute to the diagnosis and therapy of the disease. The gene expression profile of GSE64513 was downloaded from the Gene Expression Omnibus database. The dataset contained 3 FOXD3 knockout A549 lung cancer cell samples and 3 normal A549 cell samples. The differentially expressed genes (DEGs) between the FOXD3‑knockout and normal A549 cells were identified using the limma package in R. The alternative splicing genes (ASGs) in FOXD3‑knockout samples were identified by Replicate Multivariate Analysis of Transcript Splicing software. The Database for Annotation, Visualization and Integrated Discovery was used to identify the enriched functions and pathways of DEGs and ASGs. A protein‑protein interaction (PPI) network was constructed based on results from the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape software. A total of 1,853 DEGs and 2,249 ASGs were identified in FOXD3‑knockout A549 cells compared with normal A549 cells. The DEGs were enriched in 338 Gene Ontology (GO) terms and 21 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the ASGs were enriched in 470 GO terms and 22 KEGG pathways. A total of 199 overlaps between the DEGs and the ASGs were identified; a PPI network constructed based on the overlapping genes contained 97 nodes and 115 pairs. FOXD3 may serve an important role in regulating the growth, migration and proliferation of tumor cells in lung cancer. The present study indicates that a number of genes, including AURKA and NOS3, may be targets of FOXD3, mediating its effect in lung cancer.
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Copy and paste a formatted citation
Spandidos Publications style
Jiang W, Liu P and Li X: Screening of FOXD3 targets in lung cancer via bioinformatics analysis. Oncol Lett 15: 3214-3220, 2018.
APA
Jiang, W., Liu, P., & Li, X. (2018). Screening of FOXD3 targets in lung cancer via bioinformatics analysis. Oncology Letters, 15, 3214-3220. https://doi.org/10.3892/ol.2017.7685
MLA
Jiang, W., Liu, P., Li, X."Screening of FOXD3 targets in lung cancer via bioinformatics analysis". Oncology Letters 15.3 (2018): 3214-3220.
Chicago
Jiang, W., Liu, P., Li, X."Screening of FOXD3 targets in lung cancer via bioinformatics analysis". Oncology Letters 15, no. 3 (2018): 3214-3220. https://doi.org/10.3892/ol.2017.7685
Copy and paste a formatted citation
x
Spandidos Publications style
Jiang W, Liu P and Li X: Screening of FOXD3 targets in lung cancer via bioinformatics analysis. Oncol Lett 15: 3214-3220, 2018.
APA
Jiang, W., Liu, P., & Li, X. (2018). Screening of FOXD3 targets in lung cancer via bioinformatics analysis. Oncology Letters, 15, 3214-3220. https://doi.org/10.3892/ol.2017.7685
MLA
Jiang, W., Liu, P., Li, X."Screening of FOXD3 targets in lung cancer via bioinformatics analysis". Oncology Letters 15.3 (2018): 3214-3220.
Chicago
Jiang, W., Liu, P., Li, X."Screening of FOXD3 targets in lung cancer via bioinformatics analysis". Oncology Letters 15, no. 3 (2018): 3214-3220. https://doi.org/10.3892/ol.2017.7685
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