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OBJECTIVES: This study aimed to analyze the crosstalk network among T cells, epithelial cells, and fibroblasts in the tumor microenvironment of oral squamous cell carcinoma (OSCC) and to determine their prognostic values. MATERIALS AND METHODS: Single-cell subpopulation identification and communication analysis identified crosstalk markers. The least absolute shrinkage and selection operator Cox analysis identified key prognostic features by integrating the bulk transcriptome and clinical parameters. Functional analysis and immune infiltration were explored to determine possible mechanisms. RESULTS: Interactions between epithelial cells and fibroblasts primarily involve MIF, MK, PTN, IGF, EGF, and PERIOSTIN, whereas T cells interact with epithelial cells and fibroblasts through MIF, CXCL, PAR, IFN, and EGF signals. We constructed a novel prognostic feature comprising 13 crosstalk genes: HBEGF, FGF7, GRN, ITGB5, CXCR6, ERBB2, AREG, F2RL2, NAMPT, KLK12, HMGB2, TUBA1B, and KLRD1. Patients were stratified based on the RiskScore. Functional analysis revealed that the high-risk group was enriched in immunosuppressive pathways (p < 0.001). Immune checkpoints including PD-1, PD-L1, and CTLA4 were more highly expressed in the high-risk group (p < 0.05). CONCLUSIONS: The crosstalk network among T cells, epithelial cells, and fibroblasts is complex and may have implications for prognosis and clinical treatments of OSCC patients.
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This research uses panel data of cities in Jiangsu from 2009 to 2018 to construct a resilience framework that measures the level of urban resilience. A combination of the entropy method, Theil index, Moran ' sI , and the Spatial Durbin Model (SDM) is used to explore regional resilience development differences, the spatial correlation characteristics of urban resilience, and its influencing factors. The study finds that: (1) The spatial heterogeneity of regional resilience development is significant, as the overall level of resilience presents a spatial distribution pattern of descending from southern Jiangsu to central Jiangsu and to northern Jiangsu. (2) The total Theil index shows a wave-like downward trend during the study period. The differences between southern Jiangsu, central Jiangsu, and northern Jiangsu make up the main reason for the overall difference of urban resilience in Jiangsu Province. Among the three regions, the gap in resilience development level within southern Jiangsu is the largest. (3) There is a clear positive spatial correlation between urban resilience in the province and an obvious agglomeration trend of urban resilience levels. Among all subsystems, urban ecological resilience is the weakest and needs to be further improved. (4) Lastly, among the five factors affecting urban resilience, general public fiscal expenditure/GDP, which characterizes government factors, has the largest positive impact on urban resilience, while foreign trade has a negative impact. In the following studies, the theme of urban resilience should be constantly deepened, and more extensive data monitoring should be carried out for the urban system to improve the diversity of data sources, so as to assess urban resilience more accurately. Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-022-05368-x.