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Volume 16, Issue 1 (1-2026)
Iran J Ped Hematol Oncol 2026, 16(1): 745-753 |
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Ethics code: IR.ASAUMS.REC.1404.004
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Rezaeeyan H, Yousefi Chermehini N, Ahadi S, Kamali Yazdi E, Ghanavat M. The Comparison of Genes and Molecular Pathway between Newly Diagnosed and Relapsed Acute Lymphocytic Leukemia (ALL) Patients: A Bioinformatics Analysis. Iran J Ped Hematol Oncol 2026; 16 (1) :745-753
URL: http://ijpho.ssu.ac.ir/article-1-971-en.html
URL: http://ijpho.ssu.ac.ir/article-1-971-en.html
Assistant Professor of Pediatric Hematology and Oncology Department of Pediatrics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran & Assistant Professor of Pediatric Hematology and Oncology Department of Pediatrics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Abstract: (16 Views)
Background: Acute lymphoblastic leukemia (ALL) is among the most common cancers in children, which leads to the death of many patients. ALL patients include new cases and the relapsed ones. The common genes between these two conditions can largely help in managing patients and preventing future relapses. Therefore, this study investigated the genes and molecular pathways between the two conditions using bioinformatics.
Materials and Methods: In this bioinformatic study, GSE102301 database was used. After determining differentially expressed genes (DEGs), gene ontology (GO) and the related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed (using GeneCodis4 software). Interactions between proteins were evaluated using STRING database and hub genes were identified based on the highest score. Finally, ROC curve analysis was used to determine the diagnostic value of hub genes.
Results: Based on the interaction between DEGs, 10 genes were selected as hubs, which included WDR75, MYBBP1A, DDX10, URB1, HEATR1, NOP14, PUM3, VARS1, EARS2 and SYK |logFC| > 1 and p < 0.05. The results showed that all the hub genes had diagnostic value (AUC=1).
Conclusion: Hub genes identified through bioinformatics analyses may serve as potential biomarkers; however, future studies need to examine these genes in clinical settings among the patients.
Materials and Methods: In this bioinformatic study, GSE102301 database was used. After determining differentially expressed genes (DEGs), gene ontology (GO) and the related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed (using GeneCodis4 software). Interactions between proteins were evaluated using STRING database and hub genes were identified based on the highest score. Finally, ROC curve analysis was used to determine the diagnostic value of hub genes.
Results: Based on the interaction between DEGs, 10 genes were selected as hubs, which included WDR75, MYBBP1A, DDX10, URB1, HEATR1, NOP14, PUM3, VARS1, EARS2 and SYK |logFC| > 1 and p < 0.05. The results showed that all the hub genes had diagnostic value (AUC=1).
Conclusion: Hub genes identified through bioinformatics analyses may serve as potential biomarkers; however, future studies need to examine these genes in clinical settings among the patients.
Type of Study: Research |
Subject:
Oncology
Received: 2025/08/5 | Accepted: 2025/12/13 | Published: 2026/01/11
Received: 2025/08/5 | Accepted: 2025/12/13 | Published: 2026/01/11
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