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Zahra Rezvani

Zahra Rezvani

Assistant Professor

College: Faculty of Chemistry

Department: Cell and Molecular Biology

Degree: Ph.D

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Zahra Rezvani

Assistant Professor Zahra Rezvani

College: Faculty of Chemistry - Department: Cell and Molecular Biology Degree: Ph.D |

Comprehensive Bioinformatic Analysis Reveals Survival-Associated Hub Genes and miRNAs in Multiple Myeloma Patients

Authorsزهرا رضوانی,الهام هاتف,الهه سید حسینی,شکوه رحمتی پور,حامد حداد کاشانی,رضا بیات
JournalIranian Journal of Biotechnology
IFثبت نشده
Paper TypeFull Paper
Published At2025-09-21
Journal GradeScientific - research
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexISC ,JCR ,SCOPUS

Abstract

Background: Multiple myeloma (MM) is a B-cell malignancy characterized by clonal plasma cell ‎proliferation in the bone marrow. Although significant advances have been achieved in treatment, it remains ‎largely incurable, and fundamental insights at the molecular level remain to be obtained.‎ Methods: We identified and characterized the hub genes and miRNAs associated with MM by re-analyzing ‎three microarray datasets, GSE16558, GSE141260, and GSE146649, using high-throughput sequencing. We ‎re-identified DEGs using a strict filtering criterion: |logFC| ≥ 1 and p-value < 0.05. The application of the ‎Venn diagram analysis highlighted 13 common DEGs among the datasets. A total of 3211 differentially ‎expressed genes (DEGs) and 25 differentially expressed microRNAs (DEMs) were screened out, Thereafter, ‎GO and pathway enrichment of the DEGs were analyzed using FunRich software, involving biological ‎processes, cellular components, and molecular functions. The PPI network was constructed using the ‎Cytoscape software to determine the interactions among these DEGs.‎ Results: Our analyses underlined several key biological processes, including the migration of immune cells, ‎lymphocyte activation, and TGF-β signaling pathways, which play crucial roles in the progression of MM. ‎The PPI network identified a number of hub genes; among these, CCND1, ITGB1, and CREB1 were ‎significantly associated with patient survival outcomes. In addition, the interaction predictions indicated an ‎important function of miR-34c-5p and miR-155-5p in governing apoptosis, thereby promoting drug resistance ‎in MM cells. We identified 13 common DEGs across datasets, with key enrichments in immune cell migration, ‎lymphocyte activation, and TGF-β signaling. PPI analysis revealed CCND1, ITGB1, and CREB1 as top hub ‎genes, significantly linked to survival outcomes. MiRNA interactions, particularly miR-34c-5p and miR-155-‎‎5p, were implicated in apoptosis and drug resistance.‎ Conclusion: These data highlight the complex interplay between genetic alterations and the immune ‎microenvironment in MM, opening new prospects for biomarkers and therapeutic targets that may hopefully ‎improve patient management, treatment strategies, prognosis, and therapeutic resistance.‎