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Evaluation of Secretome Biomarkers in Glioblastoma Cancer Stem Cells: A Bioinformatics Analysis
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  • Ehsan Jangholi,
  • Hoda Ahmari Tehran,
  • Afsaneh Ghasemi,
  • Mohammad Hoseinian,
  • Sina Firoozi,
  • Seyed Mohammad Ghodsi,
  • Mona Tamaddon,
  • Ahmad Bereimipour,
  • Mahmoudreza Hadjighassem
Ehsan Jangholi
Tehran University of Medical Sciences
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Hoda Ahmari Tehran
Qom University of Medical Sciences
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Afsaneh Ghasemi
Fasa University of Medical Sciences
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Mohammad Hoseinian
Tehran University of Medical Sciences
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Sina Firoozi
Kermanshah University of Medical Sciences
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Seyed Mohammad Ghodsi
Tehran University of Medical Sciences
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Mona Tamaddon
Tehran University of Medical Sciences
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Ahmad Bereimipour
University of North Texas
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Mahmoudreza Hadjighassem
Tehran University of Medical Sciences

Corresponding Author:[email protected]

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Abstract

Glioblastoma (GBM) is a malignant brain tumor that frequently occurs alongside other central nervous systems (CNS) conditions. Glutamate release and aberrant cellular behavior are shared features of both CNS diseases and GBM cells. Neither their origin nor the ways in which CNS disorders affect the development or behavior of GBM are well understood. Using data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) datasets–where both healthy and cancerous samples were analyzed–we used a quantitative analytical framework to identify differentially expressed genes (DEGs) and cell signaling pathways that might be related to GBM. Then, we performed gene ontology studies and hub protein identifications to estimate the roles of these DEGs after finding disease-gene connection networks and signaling pathways. Using the GEPIA Proportional Hazard Model and the Kaplan-Meier estimator, we widened our analysis to identify the important genes that may play a role in both progression and the survival of patients with GBM. Totally, 890 DEGs, including 475 and 415 up- and down-regulated were identified, respectively. Our results revealed SQLE, DHCR7, delta-1 phospholipase C ( PLCD1), and MINPP1 genes are high expression, and the Enolase 2 ( ENO2) and hexokinase-1 ( HK1) genes are low expressions. Hence, our findings suggest novel mechanisms that affect the occurrence of GBM development, growth, and/or establishment and may also serve as secretory biomarkers for GBM prognosis and possible targets for therapy.
24 Jan 2024Reviewer(s) Assigned
01 Feb 2024Review(s) Completed, Editorial Evaluation Pending
16 Feb 2024Editorial Decision: Revise Major