The role of rare earth elements and dietary intake in tongue cancer: a mediation analysis in southeast China.

Objective: The current research aimed to examine how dietary intake and rare earth elements may affect the development of tongue cancer. Methods: The serum levels of 10 rare earth elements (REEs) in 171 cases and 171 healthy matched controls were measured by inductively coupled plasma mass spectrometry (ICP-MS). The conditional logistic regression was used to examine the relationship between dietary intake, serum levels of 10 REEs, and tongue cancer. Mediation effect and multiplicative interaction analysis were then performed to estimate the potential contribution of REEs in dietary intake associated with tongue cancer. Results: Compared with the control group, patients with tongue cancer consumed significantly less fish, seafood, fruit, green leafy vegetables, and non-green leafy vegetables, with higher serum praseodymium (Pr), dysprosium (Dy), and lanthanum (La) levels, and lower serum cerium (Ce) and scandium (Sc) levels. The interaction effect was observed between some REEs and food categories. Green vegetables' impact on the risk of tongue cancer is partially attributed to the La and Thorium (Th) elements (P < 0.05, the mediated proportion were 14.933% and 25.280%, respectively). The effect of non-green leafy vegetables for tongue cancer mediated via Pr, Dy, and Th (P < 0.05, the mediated proportion were 0.408%, 12.010%, and 8.969%, respectively), and the Sc components in seafood (P < 0.05, the mediated proportion was 26.120%) is partly responsible for their influence on the risk of tongue cancer. Conclusion: The correlation between REEs and dietary intakes for tongue cancer is compact but intricate. Some REEs interact with food intake to influence tongue cancer, while others act as a mediator.

Utility of gamma-glutamyl transpeptidase to lymphocyte count ratio in predicting prognosis of patients with oral cancer: A prospective cohort study in Southeastern China.

BACKGROUND: To assess the prognostic role of gamma-glutamyl transpeptidase to lymphocyte count ratio (GLR) and develop a prognostic nomogram for patients with oral cancer. METHODS: A prospective cohort (n = 1011) was conducted during July 2002 to March 2021 in Southeastern China. RESULTS: The median follow-up time was 3.5 years. Multivariate Cox regression (OS: HR = 1.51, 95% CI: 1.04, 2.18) and Fine-Gray model (DSS: HR = 1.68, 95% CI: 1.14, 2.49) both showed that high GLR could act as an indicator of poor prognosis. A nonlinear dose-response relationship was observed between continuous GLR and the risk of all-cause mortality (p for overall = 0.028, p for nonlinear = 0.048). Compare with TNM stage, time-dependent ROC curve proved that GLR-based nomogram model performs better in predicting prognosis (the area under curve for 1-, 3-, and 5-years mortality: 0.63, 0.65, and 0.64 vs. 0.76, 0.77, and 0.78, p < 0.001). CONCLUSION: GLR might be a useful tool in predicting prognosis for patients with oral cancer.

Development and Validation of a Robust Immune Prognostic Signature for Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is among the most destructive of tumors, leading to considerable morbidity and mortality. Abnormal immune microenvironment is closely associated with tumor progression. This study aimed to construct a robust immune prognostic model for HNSCC. The RNA-seq transcriptome data and clinical information of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) database. The key pathways and transcriptional factors (TFs) that are correlated with significantly altered immune related genes were identified. A robust immune prognostic model was constructed and further validated using a discovery-validation cohort design. An immune prognostic signature-based nomogram model was also developed. We have identified 400 significantly changed immune related genes in HNSCC. In addition, functional analysis of the altered immune related genes revealed many biological functions and pathways that might affect the tumor immune microenvironment. FOXP3, SNAI2, and STAT1 were identified as the hub TFs for regulating immunological changes in HNSCC. Moreover, an immune related gene-based prognostic signature significantly associated with the overall survival (OS) of HNSCC was constructed in the discovery cohort, and successfully validated in the validation cohort. Finally, a nomogram model based on immune prognostic signature was built and exhibited good performance for predicting the OS of HNSCC. In conclusion, the immune prognostic model is robust for predicting the prognosis of HNSCC and may evolve as a promising tool for risk evaluation and therapeutic selection.