Identification of the anticancer effects of a novel proteasome inhibitor, ixazomib, on colorectal cancer using a combined method of microarray and bioinformatics analysis

运用微阵列和生物信息学分析相结合的方法鉴定新型蛋白酶体抑制剂伊沙佐米对结直肠癌的抗癌作用

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作者:Qiaowei Fan, Bingrong Liu

Conclusion

The novel proteasome inhibitor ixazomib significantly inhibited the proliferation of human CRC SW620 cells. It exerted anticancer effects through targeting the expression of DEGs, such as HSPA6, APCDD1, TP53, and JUN, and affecting the signaling pathways including apoptosis and cell cycle pathway, which demonstrated the promising potential of ixazomib for CRC therapy.

Methods

Cell proliferation was tested by Cell Counting Kit-8 (CCK-8) assay for SW620 cells treated with different concentrations of ixazomib and different treatment times. The microarray analysis was conducted for six samples, including three samples of SW620 cells untreated with ixazomib and three samples of SW620 cells treated with ixazomib. The differentially expressed genes (DEGs) between untreated and treated samples were identified by the Linear Models for Microarray data (LIMMA) package in R language. The Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for the DEGs using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and KEGG Orthology-Based Annotation System (KOBAS) online tool. The protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and module analysis was performed for the PPI network.

Purpose

The study aimed to explore the anticancer effects of a novel proteasome inhibitor, ixazomib, on colorectal cancer (CRC) using a combined method of microarray and bioinformatics analysis. Materials and

Results

Ixazomib could inhibit the proliferation of SW620 cells in a dose-dependent and time-dependent manner. A total of 743 DEGs, including 203 upregulated DEGs such as HSPA6 and 540 downregulated DEGs such as APCDD1, were identified. Eighty-three GO terms were enriched for DEGs, which were mainly related to protein folding, apoptotic process, transcription factor activity, and proteasome. Thirty-seven KEGG pathways were perturbed, including pathway of apoptosis and cell cycle. Forty-six hub genes, such as TP53, JUN, and ITGA2, were screened out, and three modules with important functions were mined from the PPI network.

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