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. 2017 Feb 8:7:42105.
doi: 10.1038/srep42105.

Prediction of biomarkers of oral squamous cell carcinoma using microarray technology

Guang Li  1 , Xian Li  2 , Meng Yang  3 , Lvzi Xu  1 , Shixiong Deng  1 , Longke Ran  1
Affiliations

Prediction of biomarkers of oral squamous cell carcinoma using microarray technology

Guang Li et al. Sci Rep. .

Abstract

Microarray data is used to screen the genes of oral squamous cell carcinoma (OSCC). Microarray data of OSCC and normal tissues were downloaded from GEO database and analyzed with Benjamini-Hochberg (BH) method. Differentially expressed genes (DEGs) were then uploaded on DAVID database to process enrichment analysis. Target genes were finally chosen for verification experiment in vitro and in vivo. 78 DEGs were selected from 54676 genes, including 46 up- and 32 down- regulation. GO term showed that these genes were related to epidermal growth (biological processes), extracellular region (cellular components) and cytokines activity (molecular function). Protein network interaction demonstrated that OSCC was closely allied to the five key genes including CXCL10, IFI6, IFI27, ADAMTS2 and COL5A1, which was consistent with the RT-PCR data. High-expressed gene CXCL10 was chosen for further cell experiment, and the results indicated that CXCL10 can promote the proliferation, migration and invasion of normal cells and inhibited the cancer cells after si-RNA transfection. Moreover, it has been proven that CXCL10 was possibly related to the occurrence and development of OSCC. Understanding the regulation of OSCC expression will shed light on the screening of cancer biomarker.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Hierarchical clustering heat map of DEGs by normal tissues (N) and cancer tissues (C) in OSCC.
Figure 2
Figure 2. Biological process (BP), molecular function (MF) and cellular component (CC) of DEGs by function enrichment in PPI network.
Figure 3
Figure 3. Protein-protein interaction (PPI) network of DEGs by STRING.
The interaction score was set to high confidence (0.720).
Figure 4
Figure 4
(A) Five target genes expression in normal and cancer tissues, the fold change of CXCL10 was higher among these genes; (B) CXCL10 expression at different transfection time (0–72 h), the scramble siRNA sequence was employed as control, at 48 h both cells showed lower expression.
Figure 5
Figure 5. Rate of viable cells after different days (0–5d) siRNA transfection in both normal and cancer cells.
siRNA-mediated CXCL10 promoted normal cells and inhibited cancer cells proliferation.
Figure 6
Figure 6. Wound healing experiment (100 μm) with CXCL10 siRNA transfection (0–12 h).
Data and representative images were shown for normal and cancer cells. Bar charts showed the migration rate of each treatment.
Figure 7
Figure 7. Transwell assays (50 μm) of normal and cancer cells with CXCL10 siRNA (0–48 h).
The numbers of invading cells were counted, and a significant difference (P < 0.05) was observed.
See this image and copyright information in PMC

References

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