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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...

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Autores principales: Mirzaei, Tahereh, Sheikholeslami, Seyed Amir, Bereimipour, Ahmad, Jalili, Arsalan, Zali, Alireza, Sharbati, Sheida, Kaveh, Vahid, Salari, Sina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480797/
https://www.ncbi.nlm.nih.gov/pubmed/36119333
http://dx.doi.org/10.4103/jfmpc.jfmpc_1436_21
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author Mirzaei, Tahereh
Sheikholeslami, Seyed Amir
Bereimipour, Ahmad
Jalili, Arsalan
Zali, Alireza
Sharbati, Sheida
Kaveh, Vahid
Salari, Sina
author_facet Mirzaei, Tahereh
Sheikholeslami, Seyed Amir
Bereimipour, Ahmad
Jalili, Arsalan
Zali, Alireza
Sharbati, Sheida
Kaveh, Vahid
Salari, Sina
author_sort Mirzaei, Tahereh
collection PubMed
description 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.
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spelling pubmed-94807972022-09-17 Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study Mirzaei, Tahereh Sheikholeslami, Seyed Amir Bereimipour, Ahmad Jalili, Arsalan Zali, Alireza Sharbati, Sheida Kaveh, Vahid Salari, Sina J Family Med Prim Care Original Article 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. Wolters Kluwer - Medknow 2022-06 2022-06-30 /pmc/articles/PMC9480797/ /pubmed/36119333 http://dx.doi.org/10.4103/jfmpc.jfmpc_1436_21 Text en Copyright: © 2022 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Mirzaei, Tahereh
Sheikholeslami, Seyed Amir
Bereimipour, Ahmad
Jalili, Arsalan
Zali, Alireza
Sharbati, Sheida
Kaveh, Vahid
Salari, Sina
Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title_full Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title_fullStr Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title_full_unstemmed Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title_short Molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: A bioinformatics study
title_sort molecular pathways in glioblastoma-derived stem cells to identify effective drug agents: a bioinformatics study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480797/
https://www.ncbi.nlm.nih.gov/pubmed/36119333
http://dx.doi.org/10.4103/jfmpc.jfmpc_1436_21
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