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. 2020 Nov 22:2020:1705867.
doi: 10.1155/2020/1705867. eCollection 2020.

Radiosensitivity-Related Genes and Clinical Characteristics of Nasopharyngeal Carcinoma

Yongmei Dai  1   2 , Yue Zhang  3 , Mi Yang  2 , Liang Zhou  4 , Hua Pan  2 , Ting Xiao  2 , Lu Yuan  2 , Yuting Wu  2 , Min Chen  2 , Longhua Chen  2 , Jian Guan  2
Affiliations

Radiosensitivity-Related Genes and Clinical Characteristics of Nasopharyngeal Carcinoma

Yongmei Dai et al. Biomed Res Int. .

Abstract

Materials and methods: Clinicopathological data of 185 patients with NPC treated at Nanfang Hospital of Southern Medical University between January 2013 and December 2014 were retrospectively analyzed. SPSS statistical software was used to analyze the clinicopathological data related to radiotherapy efficacy. Three patients who achieved complete remission and three with disease progression after CRT were selected. Differentially expressed genes (DEGs) were screened via mRNA microarray analysis of primary diagnostic endoscopy specimens.

Results: The peripheral blood leukocyte count, platelet count, and EBV-DNA copy number in NPC patients who were resistant to radiotherapy were higher than those in NPC patients who were sensitive to radiotherapy. The RobustRankAggreg (RRA) analysis method identified 392 DEGs, and the 66 most closely related genes among the DEGs were identified from the PPI network.

Conclusion: The results of this study indicate that screening for DEGs and pathways in NPC using integrated in silico analyses can help identify a series of genetic and clinical signatures for NPC patients treated with neoadjuvant chemotherapy followed by concurrent chemoradiotherapy.

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Conflict of interest statement

We declare no competing interests.

Figures

Figure 1
Figure 1
Standardization of gene expression. The blue bar represents the data before normalization, and the red bar represents the normalized data. The abscissa represents each sample, and the ordinate represents the quantity of expression.
Figure 2
Figure 2
DEGs between two sets of samples. The upregulated genes (red dots) were selected based on FC > 2.0 and a corrected p value of <0.05. The downregulated genes (green dots) were screened based on an FC ≤ −2.0 and a corrected p value of <0.05. Genes with no significant difference in the expression are indicated by the black spot. Abbreviation: FC: fold change.
Figure 3
Figure 3
Hierarchical clustering heat map of DEGs screened based on a ∣foldchange | >2.0 and a corrected p value <0.05. The upregulated genes (red) were screened based on an FC > 2.0 and a corrected p value of <0.05. The downregulated genes (green) were screened based on an FC ≤ −2.0 and a corrected p value of <0.05. Genes with no significant difference in the expression are indicated by black boxes. Gray indicates that the signal intensity of the gene was not sufficiently high to be detected. Abbreviation: FC: fold change.
Figure 4
Figure 4
GO enrichment analysis of DEGs. Notes: The number of genes (“count”) divided by the number of total genes is the gene ratio. The size of the dots represents the number of core genes, and the color indicates the adjusted p. Only pathways with an adjusted p < 0.05 were enriched.
Figure 5
Figure 5
KEGG pathway analysis of DEGs in NPC. Notes: The number of genes (“count”) divided by the number of total genes is the gene ratio. The size of the dots represents the number of core genes, and the color indicates the adjusted p value. Only pathways with an adjusted p < 0.05 were enriched.
Figure 6
Figure 6
PPI network. Notes: The more proteins interact with each other, the larger the dot is, indicating that the more central the network is, the more critical and important the role is. Red indicates upregulated genes, and green indicates downregulated genes. Abbreviation: PPI: protein–protein interaction.
See this image and copyright information in PMC

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