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Identification of Prognostic Genes in Acute Myeloid Leukemia Microenvironment: A Bioinformatic and Experimental Analysis

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Abstract

Acute myeloid leukemia (AML) is a lethal hematologic malignancy with a variable prognosis that is highly dependent on the bone marrow microenvironment. Consequently, a better understanding of the AML microenvironment is crucial for early diagnosis, risk stratification, and personalized therapy. In recent years, the role of bioinformatics as a powerful tool in clarifying the complexities of cancer has become more prominent. Gene expression profile and clinical data of 173 AML patients were downloaded from the TCGA database, and the xCell algorithm was applied to calculate the microenvironment score (MS). Then, the correlation of MS with FAB classification, and CALGB cytogenetic risk category was investigated. Differentially expressed genes (DEGs) were identified, and the correlation analysis of DEGs with patient survival was done using univariate cox. The prognostic value of candidate prognostic DEGs was confirmed based on the GEO database. In the last step, real-time PCR was used to compare the expression of the top three prognostic genes between patients and the control group. During TCGA data analysis, 716 DEGs were identified, and survival analysis results showed that 152 DEGs had survival-related changes. In addition, the prognostic value of 31 candidate prognostic genes was confirmed by GEO data analysis. Finally, the expression analysis of FLVCR2, SMO, and CREB5 genes, the most related genes to patients’ survival, was significantly different between patients and control groups. In summary, we identified key microenvironment-related genes that influence the survival of AML patients and may serve as prognostic and therapeutic targets.

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Data Availability

The data that support the findings of this study are available from GEO database (https://www.ncbi.nlm.nih.gov/geo/) and TCGA database (https://portal.gdc.cancer.gov/), which are all publicly available.

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Acknowledgements

The authors would like to express their gratitude to Shahid Beheshti University of Medical Sciences (Tehran, Iran) for supporting this study.

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Authors and Affiliations

  1. Department of Hematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 15468-15514, Tehran, Iran

    Ali Keshavarz, Amir Abbas Navidinia, Bentol Hoda Kuhestani Dehaghi, Mohammad Hossein Mohammadi & Mehdi Allahbakhshian Farsani

  2. Department of Laboratory Sciences, School of Paramedicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

    Vahid Amiri

  3. HSCT Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Mohammad Hossein Mohammadi

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  1. Ali Keshavarz
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  2. Amir Abbas Navidinia
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Correspondence to Mehdi Allahbakhshian Farsani.

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Written consent was obtained from all participants, including patient and control individuals. The local ethics committee approved the study under the code IR.SBMU.RETECH.REC.1401.001.

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Keshavarz, A., Navidinia, A.A., Kuhestani Dehaghi, B.H. et al. Identification of Prognostic Genes in Acute Myeloid Leukemia Microenvironment: A Bioinformatic and Experimental Analysis. Mol Biotechnol (2024). https://doi.org/10.1007/s12033-024-01128-3

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