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Article in Chinese | WPRIM | ID: wpr-880142

ABSTRACT

OBJECTIVE@#To analyze gene expression profile of T cell lymphoma Jurkat cell line treated with paclitaxel by computational biology based on next generation sequencing and to explore the possible molecular mechanism of paclitaxel resistance to T cell lymphoma at gene level.@*METHODS@#IC50 of paclitaxel on Jurkat cell line was determined by CCK-8 assay. Gene expression profile of Jurkat cells treated with paclitaxel was acquired by next generation sequencing technology. Gene microarray data related to human T cell lymphoma were screened from Gene Expression Omnibus (GEO) database (including 720 cases of T cell lymphoma and 153 cases of normal tissues). Combined with the sequencing data, differential expression genes (DEGs) were intersected and screened. DAVID database was used for enrichment analysis of GO function and KEGG pathway to determine and visualize functional entries of DEGs, and protein-protein interactions network of DEGs was drawn. The levels of gene expression were detected and verified by RT-qPCR.@*RESULTS@#CCK-8 results showed that the proliferation of Jurkat cells was inhibited by paclitaxel depended on the concentration apparently. Treated by paclitaxel for 48 h, P<0.05 and |log2(FC)|≥1 were used as filter criteria on the results of RNA Sequencing (RNA-Seq) and GeoChip, 351 DEGs were found from Jurkat cells, including 323 up-regulated genes and 28 down-regulated genes. The GO functional annotation and KEGG pathway enrichment analysis showed that the role of paclitaxel was mainly concentrated in protein heterodimerization activity, nucleosome assembly and transcriptional dysregulation in cancer, etc. The results of RT-qPCR were consistent with those of the sequencing analysis, which verified the reliability of this sequencing.@*CONCLUSION@#Paclitaxel can affect the proliferation and apoptosis of T-cell lymphoma by up-regulating JUN gene, orphan nuclear receptor NR4A family genes and histone family genes.


Subject(s)
Computational Biology , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , High-Throughput Nucleotide Sequencing , Humans , Lymphoma, T-Cell , Paclitaxel , Reproducibility of Results
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