Background: Immune-related genes (IRGs) were linked to the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to identify the effects of an immune-related gene signature (IRGS) that can predict the of HNSCC prognosis. Methods: The expression data of 770 HNSCC patients from the TCGA database and the GEO database were used. To explore a predictive model, the Cox proportional hazards model was applied. The Kaplan-Meier survival analysis, as well as univariate and multivariate analyses were performed to evaluate the independent predictive value of IRGS. To explore biological functions of IRGS, enrichment analyses and pathway annotation for differentially expressed genes (DEGs) in different immune groups were applied, as well as the immune infiltration. Results: A prognostic signature comprising 27 IRGs was generated. IRGS significantly stratified HNSCC patients into high and low immune risk groups in regard to overall survival in the training cohort (HR = 3.69, 95% CI 2.73-4.98, P < 0.001). Likewise, IRGS could be linked to the prognosis of HNSCC in patients of the validation cohort (HR = 1.84, 95% CI 1.21-2.81, P < 0.01). Even after adjusting for TNM stage, IRGS was maintained as an independent predictor in the multivariate analysis (HR = 3.62, 95% CI 2.58-5.09, P < 0.001), and in the validation cohort (HR = 1.73, 95% CI 1.12-2.67, P = 0.014). The IFN-α response, the IFN-γ response, IL-2/STAT5 signaling, and IL-6/JAK/STAT3 signaling were all negatively correlated with the immune risk (P < 0.01). Immune infiltration of the high-risk group was significantly lower than that of the low-risk group (P < 0.01). Most notably, the infiltration of CD8 T cells, memory-activated CD4 T cells, and regulatory T cells was strongly upregulated in the low immune risk groups, while memory resting CD4 T cell infiltration was downregulated (P < 0.01). Conclusion: Our analysis provides a comprehensive prognosis of the immune microenvironments and outcomes for different individuals. Further studies are needed to evaluate the clinical application of this signature.
BackgroundThe evidence for association between Epstein-Barr virus (EBV) infection and risk of oral squamous cell carcinoma (OSCC) is inconsistent in the literature. Therefore, this meta-analysis was conducted to clarify this association.MethodsA literature search was conducted in electronic databases for English- and Chinese-language publications until March 31, 2017 to include eligible case-control studies. The pooled odds ratio (OR) and 95% confidence interval (95% CI) were estimated to determine the association between EBV infection and OSCC risk using a fixed- or random-effects model based on heterogeneity. Publication bias was assessed using funnel plot analysis.ResultsA total of 13 case-control studies with 686 OSCC patients and 433 controls were included based on predetermined inclusion and exclusion criteria. The pooled OR with 95% CI between EBV infection and OSCC risk was 5.03 (1.80–14.01) with significant heterogeneity observed (I2 = 87%). The subgroup analysis indicates that the year of publication, study location, economic level, sample size, tissue type, detection method and marker, control type, and language might explain potential sources of heterogeneity. Publication bias was not observed, and sensitivity analysis showed stable results.ConclusionsThe results of the current meta-analysis suggest that EBV infection is statistically associated with increased risk of OSCC. However, additional high-quality studies with larger sample sizes are needed to further confirm the relationship between EBV and OSCC.
Multilevel voltage source inverters are most promising when employed in high-power and high-voltage applications. As the number of inverter levels increases, the algorithm of space-vector pulse-width modulation (SVPWM) becomes increasingly complex. Based on the intrinsic relationship between SVPWM algorithms for 2-level inverters and those for arbitrary-level inverters, here a novel SVPWM algorithm is proposed for an arbitrary-level inverter. Considering that the nearest three vectors are used to synthesise the reference vector, the on-time of the voltage vector for an arbitrary-level inverter can be acquired from that for a 2-level inverter via the use of a linear transformation. This algorithm is verified through simulation and experiments, with the latter proving that the proposed algorithm can meet the real-time requirements of multilevel inverters.
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