Search

Background/Aim: To optimize the therapeutic potential of stem cells in stem cell therapy for neurological diseases, it is crucial to enhance the differentiation, migration, and neural network formation of stem cells, and to eliminate uncertain cell differentiation and proliferation factors. Several studies have shown that reactive oxygen species (ROS) are important factors in the regulation of neurogenesis, and Prx II (Peroxiredoxin II) is a gene that regulates ROS. Materials and Methods: As the entry point in this study to conduct a bioinformatics analysis of the sequencing results of Prx II+/+ dermal mesenchymal stem cells (DMSCs) and Prx II-/- DMSCs. lncRNA/miRNA/mRNA networks were then constructed and preliminarily verified in RT-qPCR experiments. Results: In this study, a total of 11 hub genes (Gria1, Nrcam, Sox10, Snap25, Cntn2, Dlg2, Ngf, Ntrk3, Amph, Syt1, and Cd24a), eight miRNAs (miRNA-4661, miRNA-34a, miRNA-185, miRNA-34b-5p, miRNA-34c, miRNA-449a, miRNA-449b, miRNA-449c) and 12 lncRNAs (Dubr, Gas5, Gm20427, Gm26917, Gm42547, Gm8066, Kcnq1ot1, Malat1, Mir17hg, Neat1, Rian, and Tug1) were predicted in lncRNA/miRNA/mRNA network. Conclusion: The regulatory mechanism of Prx II in the differentiation of DMSCs into neurons through ROS was explored, and a theoretical basis was determined that can be applied in future research on nervous system diseases and the clinical applications of stem cells. [ABSTRACT FROM AUTHOR]

Background/Aim: Cervical cancer (CC) is a highrisk disease in women, and advanced CC can be difficult to treat even with surgery, radiotherapy, and chemotherapy. Hence, developing more effective treatment methods is imperative. Cancer cells undergo a renewal process to escape immune surveillance and then attack the immune system. However, the underlying mechanisms remain unclear. Currently, only one immunotherapy drug has been approved by the Food and Drug Administration for CC, thus indicating the need for and importance of identifying key targets related to immunotherapy. Materials and Methods: Data on CC and normal cervical tissue samples were downloaded from the National Center for Biotechnology Information database. Transcriptome Analysis Console software was used to analyze differentially expressed genes (DEGs) in two sample groups. These DEGs were uploaded to the DAVID online analysis platform to analyze biological processes for which they were enriched. Finally, Cytoscape was used to map protein interaction and hub gene analyses. Results: A total of 165 upregulated and 362 down-regulated genes were identified. Among them, 13 hub genes were analyzed in a protein-protein interaction network using the Cytoscape software. The genes were screened out based on the betweenness centrality value and average degree of all nodes. The hub genes were as follows: ANXA1, APOE, AR, C1QC, CALML5, CD47, CTSZ, HSP90AA1, HSP90B1, NOD2, THY1, TLR4, and VIM. We identified the following 12 microRNAs (miRNAs) that target the hub genes: hsa-miR-2110, hsa-miR-92a-2-5p, hsa-miR- 520d-5p, hsa-miR-4514, hsa-miR-4692, hsa-miR-499b-5p, hsa-miR-5011-5p, hsa-miR-6847-5p, hsa-miR-8054, hsa-miR- 642a-5p, hsa-miR-940, and hsa-miR-6893-5p. Conclusion: Using bioinformatics, we identified potential miRNAs that regulated the cancer-related genes and long noncoding RNAs (lncRNAs) that regulated these miRNAs. We further elucidated the mutual regulation of mRNAs, miRNAs, and lncRNAs involved in CC occurrence and development. These findings may have major applications in the treatment of CC by immunotherapy and the development of drugs against CC. [ABSTRACT FROM AUTHOR]