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the 4th international edition and 13th Iranian Conference on Bioinformatics
international edition and Iranian Conference on Bioinformatics
صفحه اصلی
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4th international edition and 13th Iranian Conference on Bioinformatics
Identifying Key Genes, miRNAs, and lncRNAs in Lennert Lymphoma Through Comprehensive Network Analysis of Diverse Omics Data
نویسندگان :
Fatemeh Shadvar
1
1- دانشگاه الزهرا(س)
کلمات کلیدی :
Lennert lymphoma،protein-protein interaction،miRNA،lncRNA،immune system
چکیده :
Lennert lymphoma (LL) is a rare subtype of peripheral T-cell lymphoma, not otherwise specified (PTCL, NOS). This malignancy originates from T cells, which play a fundamental role in the immune system. Under normal conditions, T cells are responsible for protecting against malignancies; however, in this disease, they become malignant. This transformation creates a tumor-suppressive microenvironment, which can compromise immune function and promote tumor progression. This phenomenon underscores the dual role of T cells in pathogenesis. LL accounts for approximately 6% of non-Hodgkin lymphomas and is associated with an unfavorable prognosis, with a median overall survival of about 16 months (Patsouris et al., 1993). Consequently, understanding these dynamics is crucial for developing therapies aimed at enhancing or restoring the protective functions of the immune system. In this work, data from 10 normal samples and 12 patient samples retrieved from the GEO database (GSE132550) were analyzed to identify key biomarkers associated with Lennert lymphoma (Etebari et al., 2019). The analysis identified 405 genes with adjusted adj.P.Val<0.001 and |logFC |>8. Initially, a protein-protein interaction network for these genes was generated using the STRING database. From this network, 10 genes with the highest degree centrality FN1, VWF, MMP9, APOE, DCN, COL1A2, BGN, COL3A1, CXCL12, and LUM were identified as key hub genes. Next, miRNAs associated with these proteins were extracted from the mirDB database, and their corresponding lncRNAs were identified using the LncTarD database and a lncRNA-mRNA-miRNA network was constructed. This process resulted in the construction of a lncRNA-mRNA-miRNA triad network comprising 557 unique vertices and 1,244 edges. In the analysis of this network, miRNAs and lncRNAs with the strongest relationships to the hub proteins were identified as key biomarkers. These included microRNAs such as hsa-miR-607(associated with DCN, FN1, and COL1A2) and hsa-miR-298 (associated with DCN, FN1, and COL1A2); hsa-miR-153-5p (associated with COL1A2, COL3A1, and FN1); hsa-miR-3163 (associated with LUM, COL3A1, and FN1); and hsa-miR-4500 (associated with DCN, COL3A1, and COL1A2). Additionally, three lncRNAs AOC4P (associated with COL1A2 and MMP9), FENDRR (associated with FN1 and MMP9), and NEAT1 (associated with FN1 and MMP9) were identified as key biomarkers.This research provides valuable insights into the role of the immune system in the progression of Lennert lymphoma. Furthermore, the methodologies presented can be generalized to study other immune-related diseases and cancers.
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