RESUMEN
Oral squamous cell carcinoma (OSCC) is one of the most common malignant tumors of the head and neck with poor prognosis. This study aimed to explore the role of lnc-METRNL-1 in occurrence and prognosis of OSCC patients. Expression of lnc-METRNL-1 was compared between OSCC samples and paracancerous samples from The Cancer Genome Atlas (TCGA) database. Additionally, the lnc-METRNL-1 expression in cell lines was detected by using qRT-PCR. The overall survival (OS) was estimated based on the Kaplan-Meier and the immune cell infiltration was evaluated using CIBERSORT. Significantly enriched biological pathways were identified by Gene-set enrichment analysis (GSEA). Differential expression analysis was done in edgeR package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of differential expression genes were conducted using DAVID version 6.8. The lnc-METRNL-1 expression in OSCC was significantly lower than that in paracancerous samples, and patients with low lnc-METRNL-1 expression had poorer OS. Additionally, lnc-METRNL-1 was significantly down-regulated in OSCC cell lines compared with normal cell line. High expression of lnc-METRNL-1 was closely associated with the activation of several tumor metabolic and metabolism-related pathways. Besides, aberrant lnc-METRNL-1 expression was found to be related to the differential infiltration of immune cells in tumor tissue, such as regulatory T cells, and Macrophages. Low lnc-METRNL-1 expression was probably a poor prognostic biomarker for OSCC patients. Moreover, the potential role of lnc-METRNL-1 in the onset of OSCC was partly revealed. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03674-0.
RESUMEN
The problem of fault prognosis in the context of discrete event systems (DESs) is a crucial subject to study the security and maintenance of cyber-physical systems. In this article, the decentralized fault prognosis of partially observed DESs is analyzed with a universal state-estimate-based protocol. It follows (M,K) as the performance bound of any expected decentralized prognosers, where any fault can be predicted K steps before its occurrence and the fault is guaranteed to occur within M steps once a corresponding fault alarm is issued. To determine whether expected decentralized prognosers exist, the notion of state-estimate-coprognosability (SE-coprognosability) under the case of one fault type is proposed. Compared with existing other kinds of coprognosability, SE-coprognosability is a more generalized concept. Meanwhile, combining the formal method and algebraic state space approach, a novel state estimation algorithm is presented and based on which, the verification of SE-coprognosability is also solved.
RESUMEN
BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common maligancies of the head and neck. The prognosis was is significantly different among OSCC patients. This study aims to identify new biomarkers to establish a prognostic model to predict the survival of OSCC patients. METHODS: The mRNA expression and corresponding clinical information of OSCC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Additionally, a total of 26 hypoxia-related genes were also obtained from a previous study. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal hypoxia-related genes which were associated with the prognosis of OSCC. to establish the predictive model (Risk Score) was established for estimating the patient's overall survival (OS). Multivariate Cox regression analysis was used to determine whether the Risk Score was an independent prognostic factor. Based on all the independent prognostic factors, nomogram was established to predict the OS probability of OSCC patients. The relative proportion of 22 immune cell types in each patient was evaluated by CIBERSORT software. RESULTS: We determined that a total of four hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA were significantly associated with the prognosis of OSCC patients. The nomogram established based on all the independent factors could reliably predict the long-term OS of OSCC patients. In addition, our resluts indicated that the inferior prognosis of OSCC patients with high Risk Score might be related to the immunosuppressive microenvironments. CONCLUSION: This study shows that high expression of hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA is associated with poor prognosis in OSCC patients, and they can be used as potential markers for predicting prognosis in OSCC patients.
