The levels of IL-6 and soluble IL-33R are increased in the renal vein during surgery for clear cell renal cell carcinoma

Plasma IL-1 and IL-6 Family Cytokines with Soluble Receptor Levels at Diagnosis in Head and Neck Squamous Cell Carcinoma: High Levels Predict Decreased Five-Year Disease-Specific and Overall Survival

Activation of the acute-phase cascade (APC) has been correlated with outcomes in various cancers, including head and neck squamous cell carcinoma (HNSCC). Primary drivers of the APC are the cytokines within the interleukin-6 (IL-6) and IL-1 families. Plasma levels of IL-6 family cytokines/soluble receptors (IL-6, IL-27, IL-31, OSM, CNTF, soluble (s-)gp130, s-IL-6Rα) and IL-1 family members (IL-1RA, s-IL-33Rα) were determined at diagnosis for 87 human papillomavirus (HPV)-negative (-) HNSCC patients. We then studied the 5-year Disease-Specific Survival (DSS) and Overall Survival (OS). Increased plasma levels of IL-6 (p < 0.001/p < 0.001) (DSS/OS), IL-31 (p = 0.044/p = 0.07), IL-1RA (p = 0.004/p = 0.035), soluble (s)-IL-6Rα p = 0.022/p = 0.035), and s-gp130 (p = 0.007/p = 0.003) at diagnosis were predictors of both OS and DSS from HPV(-) HNSCC patients. The cytokine DSS/OS predictions were associated with TNM stage and smoking history, whereas the soluble receptors IL-6Rα, gp130, and IL33Rα more uniquely predicted DSS/OS. Clinically, IL-6 levels above 2.5 pg/mL yielded 75% specificity and 70% sensitivity for DSS. In conclusion, high plasma levels of IL-6, IL-31, and IL-1RA, as well as the soluble receptors IL-6Rα, gp130, and IL33Rα, predicted clinical outcome. This shows their potential as candidates for both general therapy and immune therapy stratification, as well as being future platforms for the development of new immunotherapy.

Patient-Specific Mathematical Model of the Clear Cell Renal Cell Carcinoma Microenvironment

The interactions between cells and molecules in the tumor microenvironment can give insight into the initiation and progression of tumors and their optimal treatment options. In this paper, we developed an ordinary differential equation (ODE) mathematical model of the interaction network of key players in the clear cell renal cell carcinoma (ccRCC) microenvironment. We then performed a global gradient-based sensitivity analysis to investigate the effects of the most sensitive parameters of the model on the number of cancer cells. The results indicate that parameters related to IL-6 have high a impact on cancer cell growth, such that decreasing the level of IL-6 can remarkably slow the tumor's growth.