NEW CHALCONE COMPOUND EXHIBITS MICRORNA-MEDIATED ANTICANCER PROPERTIES IN GLIOBLASTOMA
Description
This study sought to investigate the therapeutic efficacy of a new synthetic chalcone molecule, SHG-44, its cellular mechanistic actions, alongside its effects on the miRNome in U87MG and U251 glioblastoma cell line models. Our research hypothesis stated that SHG-44 would exhibit significant anti-cancer properties by modulating miRNA expression within glioblastoma cells. To test this hypothesis, we conducted small RNA sequencing (sRNA-seq) to compare miRNA expression profiles between a control group (treated with 1% DMSO) and a treated group (treated with 100µM SHG-44) in U87MG glioblastoma cells. The resulting data revealed a list of deregulated miRNAs in the presence of SHG-44, with the logFC2 values indicating the degree of upregulation or downregulation of these miRNAs compared to the DMSO control group. Our data showed that SHG-44 significantly altered the expression of various miRNAs, suggesting a potential mechanism by which this compound exerts its anti-cancer effects. Notable findings include the identification of several miRNAs that were markedly upregulated or downregulated, which could be key players in the regulatory pathways affected by SHG-44. The data can be interpreted as evidence that SHG-44 modulates miRNA expression, thereby impacting cellular pathways crucial for glioblastoma cell survival and proliferation. This detailed analysis enables other researchers to understand the specific miRNAs affected by SHG-44 and provides a basis for further investigation into the molecular mechanisms underlying its therapeutic potential.
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Steps to reproduce
The total RNA of 1% DMSO and SHG-44 (100μM) 24h treated cells were extracted with Trizol reagent (Ambion Life Technology, Aukland, New Zealand). A nanodrop bioanalyzer was used to detect the concentration of each sample (Nanodrop ND1000 Spectrophotometer, Marshall Scientific, Hampton, USA). RNA integrity was assessed using the RNA Screen Tape Kit in the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Samples with RNA integrity number (RIN) numbers greater than seven were sent off for external sRNA-seq to Biomarker Technologies (Biomarker Technologies, Inc., CA, USA). Small RNA library preparation utilised 1.5μg RNA per sample via using the NEBNext® Ultra™ Illumina kit (NEB, USA). This involved 3' and 5' adapter ligation and reverse transcription. Finally, PCR amplification and size selection enriched for small RNA libraries. Libraries were then clustered and sequenced on an Illumina HiSeq platform. Raw data was processed to remove low-quality reads and filter for lengths between 18-30 nucleotides. Clean reads were used for downstream analyses. Reads were aligned against databases to remove rRNA, tRNA, and other non-coding RNAs. Known and novel miRNAs were identified. Differential expression analysis was performed to compare miRNA levels between the DMSO and SHG-44 groups. Gene functions of miRNA targets were annotated using databases like Nr (NCBI non-redundant protein sequences: https://www.ncbi.nlm.nih.gov/refseq/); Nt (NCBI non-redundant nucleotide sequences: https://www.ncbi.nlm.nih.gov/refseq/) Pfam (Protein family: http://pfam.xfam.org); KOG/COG (Clusters of Orthologous Groups of proteins: http://www.pdg.cnb.uam.es/cursos/Leon2002/pages/software/DatabasesListNAR2002/summary/7.html#:~:text=Database%20Description,orthologs%20(direct%20evolutionary%20counterparts)); Swiss-Prot (A manually annotated and reviewed protein sequence database: https://www.uniprot.org); KO (KEGG Ortholog database: https://www.genome.jp/kegg/ko.html); GO (Gene Ontology: https://geneontology.org).