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Saeedeh Ghiasvand

Saeedeh Ghiasvand

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: science
Address:
Phone: 09120929781

Research

Title
Transcriptome analysis evinces anti-neoplastic mechanisms of hypericin: A study on U87 glioblastoma cell line
Type
JournalPaper
Keywords
HypericinU87 cell lineTranscriptome profilingApoptosis
Year
2021
Journal LIFE SCIENCES
DOI
Researchers Saeedeh Ghiasvand

Abstract

Abstract Aims Hypericin (HYP) from Hypericum perforatum has cytotoxic effects on a variety of malignant cell types, but the pattern of gene expression mediating the effect is largely unknown. Here we sought to analyze the response of U87 glioblastoma (GBM) cell lines in response to HYP. Materials and methods U87 cell line was treated by HYP. Cytotoxicity was assessed using MTT and Annexin V/PI assays. Gene expression profile was obtained using high-throughput sequencing. Enrichment analysis was performed on differentially expressed genes (DEGs). Upstream transcription factors and microRNAs regulating DEGs were predicted. The effects of DEGs on survival of GBM patients were calculated. Protein-protein interaction analysis was conducted to obtain key altered genes. The possible effect of HYP treatment on immunity response was evaluated. Key findings The IC50 of HYP on U87 cell line was determined to be 1.5 μg/ml. The main type of cell death was apoptosis. A total of 312 DEGs were found. Affected Gene Ontology terms and pathways were identified. Analysis of upstream modulators of DEGs pointed out to transcription factors that significantly overlap with GBM stem cell transcription factor. Survival analysis suggested that HYP works best for the mesenchymal subtype patients. Tumor infiltration analysis predicted that HYP may affect Treg and macrophage infiltration in vivo. Using expression pattern of GBM patients and HYP-induced DEGs we suggested Fedratinib as a complementary drug to HYP. Significance Our study represents the response of U87 cell line to HYP, with analyses on survival, transcription factors and personalization according to GBM subtype.