Comprehensive bioinformatics analysis of the mRNA profile of PLCE1 knockdown in esophageal squamous cell carcinoma

食管鳞状细胞癌中 PLCE1 敲低的 mRNA 谱的综合生物信息学分析

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作者:Xiaobin Cui, Huahua Xin, Hao Peng, Yunzhao Chen

Abstract

The authors previously reported that Phospholipase C epsilon 1 (PLCE1) exacerbated esophageal squamous cell carcinoma (ESCC), however, the underlying mechanism remains to be fully elucidated. The present study aimed to identify key differentially expressed genes (DEGs) and signaling pathways regulated by PLCE1 in ESCC. EC9706 and Eca109 cell lines were transfected with the specific small interfering (si) RNA of PLCE1, reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) and western blotting were performed to detect the expression levels of PLCE1, and subsequently, mRNA array and multiple bioinformatics analysis were conducted. RT‑qPCR was used to verify gene expression array results. The findings of the present study indicated that PLCE1 mRNA and protein expression were significantly suppressed (P<0.05) in the PLCE1 siRNA‑transfected cells. In addition, a total of 223 DEGs with >2‑fold alterations were screened between the PLCE1 siRNA‑treated cells, including 168 upregulated and 53 downregulated DEGs. In particular, inflammation or immune‑associated molecules, including Toll‑like receptor (TLR)‑4 interleukin‑6, ‑8 and chemokine C‑X‑C motif ligand 2 were significantly increased following PLCE1 knockdown. Furthermore, Gene Ontology enrichment revealed terms associated with cell proliferation, differentiation, apoptosis, signal transduction, invasion and metastasis, which may potentially be associated with PLCE1 function. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated 46 pathways were disturbed by DEGs, including focal adhesion, mitogen activated protein kinase, TLR, p53 and janus kinase/signal transducer and activator of transcription signaling pathways. The RT‑qPCR results for validation of the selected DEGs were consistent with that of the microarray data. Overall, the results of the multiple bioinformatic analysis contributes to a systematic understanding of the roles of PLCE1 in ESCC.

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