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Showing 2 results for Bioinformatics

Dr Reyhane Chamani, Mrs Parnia Sadat Pourhesseini Mahmoudabadi, Mrs Yasamin Janati, Mrs Roxana Tajdini,
Volume 12, Issue 4 (10-2022)
Abstract

Background: About 10-20% of children suffering from acute lymphoblastic leukemia (ALL), experience a relapse, which is a major cause of their death. Purine nucleotide analogs are frequently prescribed to maintain the treatment of ALL. Cytosolic 5´-nucleotidase (NT5C2) catalyzes the 5´ dephosphorylation of purine analogs. Gain-of-function mutations in the NT5C2 gene result in resistance to the treatment with purine analogs and subsequently in the relapse of the disease.
Materials and Methods: In this descriptive study, bioinformatics tools were used to assess the effect of single nucleotide polymorphisms (SNPs) in the NT5C2 gene on the function and structure of the protein. So, 352 missense variants were retrieved from the NCBI database and analyzed by SIFT, PROVEAN, PMut, PANTHER, PolyPhen2, SNPs & Go, and PhD-SNP servers. Then, structural evaluations were performed using HOPE, NetSurp-2.0, and PyMOL. Moreover, stability and evolutionary preservation were assessed by I-Mutant2.0 and ConSurf, respectively.
Results: As many as 31 nsSNPs were predicted to be affecting the protein function and stability. Also, the native residues were found to be evolutionarily preserved. The structural evaluation demonstrated that a change of hydrophobicity, flexibility, size, charge, or surface accessibility due to 24 nsSNPs would lead to the change of noncovalent interactions and then the conformation of the protein.
Conclusion: Identification of biomarkers is significant in the prediction of relapses in ALL children. In this study, bioinformatics tools served to identify 24 high-risk deleterious nsSNPs in the NT5C2 gene. These mutations can be used to predict resistance to chemotherapy and relapse in ALL patients.  

Dr Al-Hasnawi Rasool Riyadh Abdulwahid, Dr Mohammed H Mahdi, Dr Bahareh Shateri Amiri, Dr Eman Koosehlar, Dr Niloufar Kazemi, Dr Fatemeh Ghiasi, Dr Shaghayegh Ghobadi, Dr Hadi Rezaeeyan,
Volume 14, Issue 3 (7-2024)
Abstract

Background: Follicular lymphoma (FL) is a common form of non-Hodgkin lymphoma, characterized by abnormal B-cell growth within the germinal center. Research has shown the role of genes and molecular pathways in the pathogenesis of FL. However, the main factor of pathogenesis has not been determined. Therefore, in this study, the genes and molecular pathways related to the pathogenesis of FL were evaluated using a systems biology approach.
Materials and Methods: In this study (bioinformatics analysis), the GSE32018 database was used for data analysis. This database was extracted from Gene Expression Omnibus (GEO). The sample of this database was 36, which included normal and FL samples. For this purpose, 23 cases were FL and 13 were healthy samples. Protein-protein interaction (PPI) is performed to show the interaction between DEGs. STRING software is used for this purpose. Associations between the hub genes, transcription factors, and microRNAs were assessed using the miRTarBase and TRRUST databases. The criteria used for data analysis included log fold change greater than one and p < 0.05.
Results: After evaluating and analyzing the data, the results showed that 866 DEGs were identified between the control and FL samples. Of this population, 231 cases of UP regulation and 635 cases of downregulation were in FL samples compared to control samples. PPI network and hub gene analyses identified 7 hub genes, including RPL37A, MRPS7, RPS14, RPS28, RPL34, RPS20, and RPS3. According to the results, hsa-miR-191-5p has the highest interactions with hub genes among miRNAs, and KDM5A has the most interactions among TFs. Conclusion: Identifying genes and molecular pathways can be effective in designing therapeutic strategies and preventing the proliferation of FL cells, thereby increasing patients’ survival.


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