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<p>Acute Myeloid Leukemia (AML) patient-derived Mesenchymal Stem Cells (MSCs) behave differently than normal ones, creating a more protective environment for leukemia cells, making relapse harder to prevent. This study aimed to identify prognostic biomarkers and elucidate relevant biological pathways in AML by leveraging microarray data and advanced bioinformatics techniques. We retrieved the GSE122917 dataset from the NCBI Gene Expression Omnibus and performed differential expression analysis (DEA) within R Studio to identify differentially expressed genes (DEGs) among healthy donors, newly diagnosed AML patients, and relapsed AML patients. Data normalization and DEA were achieved using the PLIER method and Plotrix package, with quality assessment performed through visual box plots. Functional enrichment analyses and KEGG pathway analysis illuminated the biological processes associated with DEGs. Network interactions were visualized using Cytoscape software. Survival analysis is performed through Kaplan–Meier plotter. Our analysis revealed a significant downregulation of <i>NCAPG</i>, <i>UBE2C</i>, <i>CDC20</i>, and <i>CDK1</i>, alongside the upregulation of <i>SPP1</i>, as key genes implicated in both the initiation and relapse phases of AML. Survival analysis indicated that lower expression levels of <i>NCAPG</i>, <i>UBE2C</i>, <i>CDC20</i>, and <i>CDK1</i>, and higher levels of <i>SPP1</i>, were correlated with poorer event-free survival (EFS). Additionally, the study highlighted the cell cycle as pivotal in leukemia initiation and progression, while the p53 pathway emerged as critical during the relapse phase. Our findings suggest that <i>NCAPG</i>, <i>UBE2C</i>, <i>CDC20</i>, <i>CDK1</i>, and <i>SPP1</i> may serve as prognostic biomarkers for AML management, especially through their interaction with the p53 pathway in disease progression. These insights underscore the potential for targeting the p53 pathway and integrating these biomarkers to enhance outcomes for AML patients.</p>

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Deciphering the molecular landscape of acute myeloid leukemia initiation and relapse: a systems biology approach

  • 期刊论文

  • 发表日期：

    2025年9月10日

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  • Atefeh Bahmei,
  • Hanieh Fadakar,
  • Gholamhossein Tamaddon

摘要

Acute Myeloid Leukemia (AML) patient-derived Mesenchymal Stem Cells (MSCs) behave differently than normal ones, creating a more protective environment for leukemia cells, making relapse harder to prevent. This study aimed to identify prognostic biomarkers and elucidate relevant biological pathways in AML by leveraging microarray data and advanced bioinformatics techniques. We retrieved the GSE122917 dataset from the NCBI Gene Expression Omnibus and performed differential expression analysis (DEA) within R Studio to identify differentially expressed genes (DEGs) among healthy donors, newly diagnosed AML patients, and relapsed AML patients. Data normalization and DEA were achieved using the PLIER method and Plotrix package, with quality assessment performed through visual box plots. Functional enrichment analyses and KEGG pathway analysis illuminated the biological processes associated with DEGs. Network interactions were visualized using Cytoscape software. Survival analysis is performed through Kaplan–Meier plotter. Our analysis revealed a significant downregulation of NCAPG, UBE2C, CDC20, and CDK1, alongside the upregulation of SPP1, as key genes implicated in both the initiation and relapse phases of AML. Survival analysis indicated that lower expression levels of NCAPG, UBE2C, CDC20, and CDK1, and higher levels of SPP1, were correlated with poorer event-free survival (EFS). Additionally, the study highlighted the cell cycle as pivotal in leukemia initiation and progression, while the p53 pathway emerged as critical during the relapse phase. Our findings suggest that NCAPG, UBE2C, CDC20, CDK1, and SPP1 may serve as prognostic biomarkers for AML management, especially through their interaction with the p53 pathway in disease progression. These insights underscore the potential for targeting the p53 pathway and integrating these biomarkers to enhance outcomes for AML patients.