Background: Glioblastoma (GBM), with its high recurrence and mortality rates, makes it the deadliest neurological malignancy. Oxidative phosphorylation is a highly active cellular pathway in GBM, and NFYB is a tumor-associated transcription factor. Both are related to mitochondrial function, but studies on their relationship with GBM at the single-cell level are still scarce.Methods: We re-analyzed the single-cell profiles of GBM from patients with different subtypes by single-cell transcriptomic analysis and further subdivided the large population of Glioma cells into different subpopulations, explored the interrelationships and active pathways among cell stages and clinical subtypes of the populations, and investigated the relationship between the transcription factor NFYB of the key subpopulations and GBM, searching for the prognostic genes of GBM related to NFYB, and verified by experiments.Results: Glioma cells and their C5 subpopulation had the highest percentage of G2M staging and rGBM, which we hypothesized might be related to the higher dividing and proliferating ability of both Glioma and C5 subpopulations. Oxidative phosphorylation pathway activity is elevated in both the Glioma and C5 subgroup, and NFYB is a key transcription factor for the C5 subgroup, suggesting its possible involvement in GBM proliferation and recurrence, and its close association with mitochondrial function. We also identified 13 prognostic genes associated with NFYB, of which MEM60 may cause GBM patients to have a poor prognosis by promoting GBM proliferation and drug resistance. Knockdown of the NFYB was found to contribute to the inhibition of proliferation, invasion, and migration of GBM cells.Conclusion: These findings help to elucidate the key mechanisms of mitochondrial function in GBM progression and recurrence, and to establish a new prognostic model and therapeutic target based on NFYB.

N-7 methylguanine (m7G) is one of the most common RNA base modifications in post-transcriptional regulation, which participates in multiple processes such as transcription, mRNA splicing and translation during the mRNA life cycle. However, its expression and prognostic value in uterine corpus endometrial carcinoma (UCEC) have not been systematically studied. In this paper, the data such as gene expression profiles, clinical data of UCEC patients, somatic mutations and copy number variants (CNVs) are obtained from the cancer genome atlas (TCGA) and UCSC Xena. By analyzing the expression differences of m7G-related mRNA in UCEC and plotting the correlation network maps, a risk score model composed of four m7G-related mRNAs (NSUN2, NUDT3, LARP1 and NCBP3) is constructed using least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression in order to identify prognosis and immune response. The correlation of clinical prognosis is analyzed between the m7G-related mRNA and UCEC via Kaplan–Meier method, receiver operating characteristic (ROC) curve, principal component analysis (PCA), t-SNE, decision curve analysis (DCA) curve and nomogram etc. It is concluded that the high risk is significantly correlated with (P < 0.001) the poorer overall survival (OS) in patients with UCEC. It is one of the independent risk factors affecting the OS. Differentially expressed genes are identified by R software in the high and low risk groups. The functional analysis and pathway enrichment analysis have been performed. Single sample gene set enrichment analysis (ssGSEA), immune checkpoints, m6A-related genes, tumor mutation burden (TMB), stem cell correlation, tumor immune dysfunction and rejection (TIDE) scores and drug sensitivity are also used to study the risk model. In addition, we have obtained 3 genotypes based on consensus clustering, which are significantly related to (P < 0.001) the OS and progression-free survival (PFS). The deconvolution algorithm (CIBERSORT) is applied to calculate the proportion of 22 tumor infiltrating immune cells (TIC) in UCEC patients and the estimation algorithm (ESTIMATE) is applied to work out the number of immune and matrix components. In summary, m7G-related mRNA may become a potential biomarker for UCEC prognosis, which may promote UCEC occurrence and development by regulating cell cycles and immune cell infiltration. It is expected to become a potential therapeutic target of UECE.

Background: By using network pharmacology and molecular docking technology, we have explored the mechanism of action of Sanqi in the treatment of endometriosis (EMS), in order to provide reference for clinical studies of Chinese medicine treatment of Ems and Chinese medicine pharmacology. Methods: There are 123 intersecting targets between the active ingredients of Sanqi and disease targets. In the Protein-Protein Interaction network, Jun proto-oncogene, AP-1 transcription factor subunit, tumor necrosis factor, interleukin 6, etc., are the core proteins. The top 20 genes ranked by degree have been analyzed according to the Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analysis, and 20 pathways have been identified. Results: On the Kyoto Encyclopedia of Genes and Genomes pathway, the most important part is the phosphatidylinositol 3’-kinase-Akt signaling pathway, and on the Gene Ontology pathway, it is the Heme binding. The top 3 targets docked to quercetin have a certain affinity when it is docked to their degree value. Among the chemical components of Sanqi, quercetin has the most targets, suggesting that it may play a major role in the treatment of EMS. Conclusion: The results of molecular docking provide further evidence of the potential role of Sanqi for EMS. Overall, our study provides a new direction for the treatment of EMS and provides the basis for Sanqi as a drug for the treatment of EMS.

Necroptosis, a programmed form of necrotic cell death, plays critical regulatory roles in the progression and metastatic spread of cancers such as cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, there are few articles systematically analyzing the necroptosis-related long non-coding RNAs (NRlncRNAs) correlated with CESC patients. Both RNA-sequencing and clinical data of CESC patients are downloaded from TCGA database in this study. Pearson correlation analysis, least absolute shrinkage, operator algorithm selection and Cox regression model are employed to screen and create a risk score model of eleven-NRlncRNAs (MIR100HG, LINC00996, SNHG30, LINC02688, HCG15, TUBA3FP, MIAT, DBH-AS1, ERICH6-AS1SCAT1, LINC01702) prognostic. Thereafter, a series of tests are carried out in sequence to evaluate the model for independent prognostic value. Gene set enrichment analytic paper, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analytic paper make it clear that immune-related signaling pathways are very rich in the high-risk subgroup. Additionally, the prognostic risk score model is correlated to immune cell infiltration, potential immune checkpoint, immune function, immune micro-environmental and m6A-related gene. Mutation frequency in mutated genes and survival probability trend are higher in the low-risk subgroup in most of test cases when compared to the high-risk subgroup. This study constructs a renewed prognostic model of eleven-NRlncRNAs, which may make some contribution to accurately predicting the prognosis and the immune response from CESC patients, and improve the recognition of CESC patients and optimize customized treatment regimens to some extent.

Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC.