Objectives. The necessity to develop a method for prognostication and to identify novel biomarkers for personalized medicine in patients with head and neck squamous cell carcinoma (HNSCC) cannot be overstated. Recently, pathomics, which relies on quantitative analysis of medical imaging, has come to the forefront. CXCL8, an essential inflammatory cytokine, has been shown to correlate with overall survival (OS). This study examined the relationship between CXCL8 mRNA expression and pathomics features and aimed to explore the biological underpinnings of CXCL8.Methods. Clinical information and transcripts per million mRNA sequencing data were obtained from The Cancer Genome Atlas (TCGA)-HNSCC dataset. We identified correlations between CXCL8 mRNA expression and patient survival rates using a Kaplan-Meier survival curve. A retrospective analysis of 313 samples diagnosed with HNSCC in the TCGA database was conducted. Pathomics features were extracted from hematoxylin and eosin–stained images, and then the minimum redundancy maximum relevance, with recursive feature elimination (mRMR-RFE) method was applied, followed by screening with the logistic regression algorithm.Results. Kaplan-Meier curves indicated that high expression of CXCL8 was significantly associated with decreased OS. The logistic regression pathomics model incorporated 16 radiomics features identified by the mRMR-RFE method in the training set and demonstrated strong performance in the testing set. Calibration plots showed that the probability of high gene expression predicted by the pathomics model was in good agreement with actual observations, suggesting the model’s high clinical applicability.Conclusion. The pathomics model of CXCL8 mRNA expression serves as an effective tool for predicting prognosis in patients with HNSCC and can aid in clinical decision-making. Elevated levels of CXCL8 expression may lead to reduced DNA damage and are associated with a pro-inflammatory tumor microenvironment, offering a potential therapeutic target.

Objectives: Given the emerging role of peroxisome proliferator-activated receptor gamma (PPARgamma) in immune regulation and the increasing prevalence of allergic rhinitis (AR), we sought to understand how modulation of the PPARgamma pathway impacts the balance of CD4⁺ T-cell subsets, particularly regulatory T cells (Tregs) and T helper (TH)1, TH2, and TH17 cells, which are key players in the pathogenesis of AR. This knowledge is crucial for developing novel therapeutic strategies targeting the PPARgamma-CD4⁺ T-cell axis to manage AR more effectively. Methods: We used PPARgamma^f/fLyz2-Cre mice for PPARgamma deletion. In an ovalbumin (OVA)-induced AR mouse model, PPARgamma^+/-f/fLyz2-Cre mice were assessed for allergic symptoms, splenic Tregs, and nasal eosinophils. Additionally, the effects of a PPARgamma agonist on the polarization of naïve CD4⁺ T cells were examined. Results: PPARgamma^+/-f/fLyz2-Cre mice showed worsened allergic symptoms, reduced splenic Tregs, and increased nasal mucosa eosinophilic infiltration. PPARgamma agonist treatment promoted naïve CD4⁺ T-cell polarization into Tregs and inhibited their differentiation into TH1, TH2, and TH17 subsets. Conclusions: Our findings indicate that PPARgamma plays a crucial role in regulating TH-cell subsets in AR. PPARgamma agonists could be a potential therapeutic strategy to mitigate allergic inflammation in AR by promoting Treg development and suppressing pathogenic TH-cell responses.