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Objective: Dysregulation of Toll-like receptor signaling and increased proportions of Th17 and other T helper cells can facilitate esophageal squamous cell carcinoma (ESCC) progression. Methods: By integrating WGCNA, Limma, and artificial intelligence (AI, including LASSO-Cox regression and SOM) frameworks, we first identified a Toll-like receptor signaling and Th17 and T helper cell (ThpT)-related prognostic model and Thp molecular subgroups for ESCC patients in bulk transcriptomic profiles. Next, Thp-associated hub genes were identified, followed by evaluation of corresponding molecular and immune features. Indeed, the heterogeneity of ESCC was estimated using a single-cell transcriptomic dataset acquired from the GEO database. Furthermore, we also evaluated Thp-associated hub gene molecular and biological functions in spatial and temporal manners on targeted cells via pseudotime trajectory and AI-driven targeted gene knockout (KO). ESCC therapeutic agents targeting Thp-associated hub genes were enriched via a drug–gene network and then examined by ridge regression-driven drug sensitivity estimation and molecular docking. To enhance the robustness of our study, we performed in vitro studies to quantify the relationship of the targeted gene with Th17 and ESCC progression. Results: Based on Thp, we successfully identified a prognostic model and molecular subgroups of ESCC patients. DDX39A and PBK should be considered ThpT-related hub genes involved in ESCC progression and decreased infiltration of Th17 cells. Based on drug sensitivity estimation and molecular docking, bleomycin and talazoparib may be potential drugs for treating esophageal squamous cell carcinoma. Conclusions: ThpT can guide personalized and precision medicine for ESCC patients. Our study provides a novel clinical translation strategy for combating ESCC.
Liu et al. (Tue,) studied this question.