Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study.

Background and Aim: Glioblastoma multiform (GBM) is considered as one of the malignant brain tumors that affect a wide range of people every year. Cancer stem cells, as essential factors, are resistant to chemotherapy drugs and complicate treatments. Therefore, finding critical molecular pathways in GBM-derived stem cells, and selecting the appropriate drug agents can prove more effective treatment approaches for GBM. Method: In this study, using RNA-Seq data, we performed continuous bioinformatics analyses and examined the up-and down-regulated genes from GBM-derived stem cells samples. Afterward, we separated the signaling pathways using the KEGG database and measured the protein interactions with the STRING database. Then, using the Drug matrix database, we nominated drugs that could affect these genes. Results: The first 20 pathways on tumorigenesis and 41 up-regulated and 73 down-regulated genes were selected. These genes were most active in the pathways involved in cell division, metabolism, cytoskeleton, cell adhesion molecules, and extracellular space. We then examined the candidate genes and the approach of the drugs that target these genes. Chlorambucil, cyclosporine A, doxorubicin, and etoposide were selected as the drug agents. Conclusion: Using integrated bioinformatics analyses, it was found that prominent genes in the cell cycle and cytoskeletal pathways are more expressed in cancer stem cells and that Chlorambucil, cyclosporine A, doxorubicin, and etoposide can be effective compounds to attenuate these cells.

Investigating the molecular mechanisms of Tamoxifen on the EMT pathway among patients with breast cancer.

Tamoxifen is one of the most used drugs for breast cancer. This study aimed to investigate the effect of the Tamoxifen mechanism on the epithelial-mesenchymal transition (EMT) pathway among breast cancer patients due to its resistance to breast cancer cells. We selected the appropriate datasets from the GEO database using continuous and integrated bioinformatics analysis. We examined the signaling pathways, gene ontology, and protein association of genes after classifying the gene expression profile. Finally, we confirmed the candidate genes using the GEPIA database. Two groups were defined for gene expression profiles. The first group in which the expression profile of genes increased after Tamoxifen was evaluated using the expression profile of genes that decreased in the EMT pathway. The second group was the opposite of the first group. 253 genes in the first group and 302 genes in the second group were shared. The genes in the first group were involved in various pathways of cell death, focal adhesion, and cellular aging. The second group was more involved in different phases of the cell cycle. Finally, MYLK, SOCS3, and STAT5B proteins from the first group and BIRC5, PLK1, and RAPGAP1 proteins from the second group were selected as candidate proteins in connection with the effect of Tamoxifen on the EMT pathway. We evaluated Tamoxifen's effect on the EMT pathway more accurately. However, for a closer look at Tamoxifen, more studies need to be done on target genes and proteins to clarify their role.